AIRO Young Opportunities

Do you know of more opportunities?

Let us know using the form below, filling in our form, or posting to our group.

Your name
Your email
Title
Url

Refine your search

Search

  Only look for open opportunities
  Only look for opportunities in academia
  Only look for opportunities in the industry

Displaying opportunities 226 - 250 of 382 in total
Expires Title Institution Country Link Type
30 Jun 2017 PhD Positions at OrangeLab

Toggle description

We are offering a 3-years PhD thesis in Operations Research on "Optimal
planning of wireless networks". This student will work 80% of the time at
Orange labs, Paris, and 20% of the time at the Laboratoire d'Informatique
d'Avignon. The net salary is rough 2000€ per month.

We are looking for an outstanding student with good programming skills, a
good level of Operations Research, and some interest in networks (knowledge
in robust optimization or stochastic programming is a plus). The interested
students must send their CV (including marks, ranking, and recommendation
letters) to rosa.figueiredo@univ-avignon.fr. Knowledge of French is not
necessary but would ease the integration of the student at Orange labs.

The thesis will be co-advised by Matthieu Chardy, Rosa Figueiredo, Adam
Ouorou, and Michael Poss. More information on the topic of the thesis can
be found here https://orange.jobs/jobs/offer.do?joid=61998&lang=FR

Please contact rosa.figueiredo@univ-avignon.fr before applying on the
website.

OrangeLab and University of Avignone France Go Industry
30 Jun 2017 PhD Positions in Statistics and Operational Research for Industry

Toggle description

PhD studentships for UK and EU nationals are available in "Statistics and Operational Research for Industry" (STOR-i), Lancaster University, UK, for October 2017 entry.

STOR-i is a pioneering 4 year MRes/PhD programme established in 2010. Using industrial challenges as the catalyst for mathematical innovation, the centre develops future international research leaders. Industrial partners include AstraZeneca, ATASS, BT, IBM, Rolls-Royce and Shell. Our PhD projects involve substantial collaboration with our industrial partners, providing a unique research and training experience. The cohort-based PhD programme offers a unique style of PhD training, which provides an opportunity to:

- be part of an exciting new group of researchers;
- co-operate and interact with like-minded peers;
- work directly with leading industry partners;
- open up real potential for rapid career progression;
- make significant scientific and industrial impact with your research.

The studentships include tuition and a tax-free enhanced maintenance grant of approximately £16,296. On successful completion of the MRes, this will rise to £17,296 per year, or £19,296, for students undertaking an industry funded PhD.

Due to demand for places, early applications are strongly encouraged. To find out more please visit http://www.stor-i.lancs.ac.uk/apply or contact us at stor-i@lancaster.ac.uk.

Lancaster University United Kingdom Go Academia
30 Jun 2017 Industrial PhD positions in Operational Research and Machine Learning

Toggle description

We invite applications for a fully funded PhD position in Operations Research and Machine Learning. The PhD should start no later than October 2017.

Title: demand models and schedule design for airlines

Operations Research has been successfully optimizing airline industry processes for more than sixty years. The topic of "schedule design" provides tools to decide which market to serve, with what frequency, and how to schedule flight legs to meet these frequencies. Mathematically, this requires to model demand and customer preferences, and then find the set of flight legs to operate that maximizes the predicted profit.

Two recent trends challenge the traditional approaches to schedule design. First, the air transportation industry moved from a monopolistic to a very competitive environment, which calls for a new generation of demand models. Second, the amount of data made available by information technologies opens new opportunities to better take into account the uncertainty of demand. These new stochastic models notably enable to evaluate and control risk when optimizing the flight legs schedule.

The objective of this PhD is to set up new approaches to schedule design that responds to these challenges.

* Research supervision and environment
Scientific supervisors: Frédéric Meunier and Axel Parmentier

This PhD takes place in the context of the Operations Research and Machine Learning chair between Air France and the Ecole des Ponts Paristech. The candidate will share its time between the Cermics, the applied mathematics center of the Ecole des Ponts Paristech, and the Operations Research department of Air France.

Ecole des Ponts Paristech is one of the top French universities, and Paris provides a startling research environment in mathematics and computer science.

* Candidate profile
Students are expected to carry out top-level research. They will develop efficient solution algorithms to difficult planning problems. They must have a master degree in Operations Research, Applied Mathematics, Computer Science, or a related field. They should demonstrate good programming skills. Knowledge of mathematical programming is required, experience in stochastic optimization, machine learning, or game theory is an asset. Even though they may learn French during their stay, French knowledge is not mandatory.

* Application procedure
Interested candidates should send their application package electronically to Axel Parmentier (axel.parmentier@enpc.fr). The application should contain the following documents:
- Cover letter explaining the motivation for the PhD, your research/career interests, as well as your preferred starting date
- Detailed curriculum vitae with list of publications (if any)
- Grade records of Bachelor and Master programs
- Reference letters or contact details of references (one of them should be the supervisor of the candidate's Master studies)

Applications are opened from now. The position is limited to three years. If you have further questions regarding this position, please contact Axel Parmentier (axel.parmentier@enpc.fr).
Position will remain available until filled.

Air France and Paristech France Go Industry
30 Jun 2017 PhD position in Computer Science and Optimisation

Toggle description

Information Structures in Complex Queueing Systems

Strategic decisions in queueing systems are very common in everyday life. Rooms in hospitals, voting locations, security gates at international airports and amusements parks are many examples of systems for which strategic decisions are taken by each customer in order to join optimally those systems [1].

The analysis methods and techniques for studying such decision processes in complex queueing systems are mainly described in the book [2]. An interesting new aspect of these problems is to study the impact of the information structure onto the strategic decisions and equilibrium of the customers. Information about the system like the actual queue length and/or processing rate is an important parameter for customers who face the decision whether to join or to choose a particular option/system. Moreover, customers are not all equal faced to the information proposed. Some of them can have easily access to the information and some not. Even, the system manager may aim to hide some information to customers. A recent paper [3] has shown that some simple policies like giving all the information or nothing are optimal in some particular cases.

The aim of this project is to extend those results for more complex structure of the system.

Backgrounds: The candidate should have good knowledge in Mathematics, stochastic models and optimization techniques. Some basic skills in programming and simulations are also welcomed.

Starting: September 1^st 2017.

Location: University of Avignon, LIA, France.

Supervisor: Professor Y. Hayel, CERI/LIA University of Avignon, France. yezekael.hayel@univ-avignon.fr

[1] H. Rafael, R.-G. Ricky, Equilibrium in a two dimensional queueing game: When inspecting the queue is costly, Working paper.
[2] R. Hassin, M. Haviv, To queue or not to queue: Equilibrium behavior in queueing systems, Vol. 59, Springer Science & Business Media, 2003.
[3] E. Simhon, Y. Hayel, D. Starobinski, Q. Zhu, Optimal Information Disclosure Policies in Strategic Queueing Games, in Operation Research Letters, vol. 44, no. 1, 2016.

University of Avignon France Go Academia
30 Jun 2017 PhD position in Operational Research

Toggle description

A PhD position in Operations research is available at INRIA Lille (France) in the INOCS team : https://team.inria.fr/inocs/ and Ecole Polytechnique de Montréal



Title : A Leader-Follower Framework for Demand Response
Keywords Optimization, operations research, Energy

The PhD thesis will be done according to a co-tutelle agreement between Ecole Polytechnique de Montreal and Centrale Lille. It will be partly supported (50%) by Canada

Scientific supervisors: Luce.Brotcorne@inria.fr , frederic.semet@inria.fr , miguelf.anjos@polymtl.ca

To apply, please send a cv and a motivation letter to the scientific supervisors

Electricity is a critical source of energy for our society. The smart grid encompasses the developments concerning the power system that are taking place, or need to take place, for the system to better meet the needs and expectations of society in the 21st century. However it also brings up new challenges to operate the resulting system. These include using the power grid already in place more efficiently, integrating renewable energy sources such as wind and solar power generation, managing the flows of power and of information, and integrating loads as active participants in the grid operations.

A central challenge in the full implementation of the smart grid is the effective integration of the customers as active participants in the grid, a process generally referred to as demand response. This includes every means available to support an active role of the loads in shaping the load curve of the grid: peak clipping, valley filling, load shifting, strategic conservation, strategic load growth, and flexible load shape. Although direct load control can be effective to handle a small number of large loads, it is certainly not practical for managing demand response in the smart grid of the future.

The objective of the proposed research is to design and implement a new framework to ensure the economic efficiency of the provision of demand response . This research is set in a context where companies providing energy via the power grid, such as utilities and virtual power plants, can use dynamic electricity pricing to incentivize their customers to shift all or part of their loads from the peak periods to off peak periods so as to adjust the load curve in a way that facilitates the operation of the power grid.

We will capture the economic aspects of this context using a leader-follower framework . This is a wellknown game-theoretic framework applicable to situations where there are two decision levels with conflicting objectives. In its simplest form, there are two players, namely the leader and the follower. The leader and fully controls a set of variables that represents its decisions, and the follower solves an optimization problem according to its own interests, but taking the leader's decisions as given. The resulting model is a bilevel optimization problem.

Bilevel optimization is a difficult class of problems; indeed all leader-follower frameworks lead to intrinsically difficult problems. Thus it is imperative to take exploit the characteristics of the speciffc application to formulate and solve these problems.

INRIA Lille and Ecole Polytechnique de Montreal France and Canada Go Academia
30 Jun 2017 PhD positions in Operational Research and Machine Learning

Toggle description

We invite applications for fully funded Ph.D. positions in Montreal in the
domain of Operations Research, as well as in the intersection between
Operations Research and Machine Learning. These positions aim at advancing
our collective capabilities to solve hard optimization problems and our
understanding of how external data sources and real-time data can be used
to improve the decision-making process. Earliest starting dates are
September 2017 and January 2018.

* Research Topics
Research topics may be aligned with the interests of the students. Several
pre-defined research projects are also available (some of them in
collaboration with industrial partners). Topics may generally include the
following:
- Large-scale optimization for dynamic (combinatorial) planning problems
(e.g. Benders decomposition, Column Generation, Lagrangian Relaxation)
- Optimization under uncertainty (e.g. stochastic programming, robust
optimization, improvement of uncertainty sets and scenario generation
through external data)
- Improvement of (à priori and real-time) planning through integration of
external data sources via machine learning
- Development of Operations Research based algorithms to efficiently solve
machine learning problems

Research may be fundamental, applied, or a mix of both. Applications may
include domains such as Logistics and Transportation (e.g., vehicle sharing
systems, facility location, traffic management), Telecommunications and
Revenue Management (e.g., assortment planning).

* Research supervision and environment
The students will work under the supervision of Dr. Sanjay Dominik Jena,
professor at the Department of Management and Technology (
mantech.esg.uqam.ca) at the Management School of Université du Québec à
Montréal (École des Science de la Gestion, UQAM). Sanjay Dominik Jena is
also member of the worldwide renowed, Montreal-based research center
CIRRELT (www.cirrelt.ca) and the Canada Exellence Research Chair in Data
Science for Real-time Decision-making (www.cerc-datascience.polymtl.ca).
Students may be co-supervised by other members of these research centers
and will be registered either at the joint Ph.D. program in Management
(including ESG UQAM, HEC Montréal, McGill and Concordia) or at the
respective university of the other supervisor(s).

Montreal is a dynamic Metropolis, located in the province of Québec,
Canada. The city is bilingual (French/English) and known for its
international atmosphere. Montreal is known for its vibrate research
environment, hosting five major universities and several research centers
in the domains of Operations Research and Machine Learning. The successful
candidates will be working in one of the above-mentioned research centers.

* Candidate profile
Students are expected to carry out top-level research. They will develop
efficient solution algorithms to difficult planning problems such as those
in the above-listed domains. Candidates should have a Masters degree (or
equivalent) in Computer Science, Operations Research, Applied Mathematics,
or a related field. They should demonstrate good programming skills.
Experience in mathematical programming, machine learning, or data analysis
is an asset. Candidates should possess a good level of written and oral
English. Even though they may eventually learn French during their stay,
French knowledge is not obligatory.

* Application procedure
Interested candidates should send their application package electronically
to Sanjay Dominik Jena (sanjay.jena@cirrelt.ca). The application should
contain the following documents:
- Cover letter explaining the motivation to perform a Ph.D. in one of the
domains mentioned above in Montreal, your research interests, as well as
your preferred starting date
- Detailed curriculum vitae with list of publications (if any)
- Grade records of Bachelor and Master programs
- Reference letters or contact details of references (one of them should be
the supervisor of the candidate's Master studies)

If you have further questions regarding these positions, possible research
topics, etc., please contact Sanjay Dominik Jena (sanjay.jena@cirrelt.ca).
Positions will remain available until filled.

CIRRELT Canada Go Academia
30 Jun 2017 PhD positions in Data Science, Industrial Engineering, Operational Research, Computer Science

Toggle description



The research group in Health Care Management of the School of Mines in Saint-Etienne is seeking a PhD candidate in Data Science and/or Industrial Engineering and/or Operational Research and/or Computer Science

Subject Title : Medical decision analytics using health data: application to the lung cancer case study
Supervisors: Vincent Augusto, Xiaolan Xie and Raksmey Phan
Structure: Mines Saint-Etienne, UMR CNRS 6158 LIMOS
Location: 158 cours Fauriel 42023 Saint-Etienne cedex 2 France
Starting date: October 1 st 2017

Subject
Data analytics consists in developing optimization and/or machine learning based algorithms that learn
to recognize complex patterns within valuable and massive data. Challenges related to that topic are
numerous, and many scientific fields are involved: computer science, data science, operational
research, process and data mining.
When applied to health-care, the objectives are often summarized as improving quality and timeliness
of care, maximizing financial performance, and decreasing practice variability across organizations. It
relies on the following tasks: (i) identify critical features that impact outcomes (allocation of limited
resources/time for greater effect); (ii) seek greater use of treatment evidence to advance the quality
and effectiveness of care delivery; (iii) rapid learning and best practice dissemination. Process mining
is also a closely connected field of research (van der Aalst 2004).
The main objective of this thesis consists in developing innovative optimization and machine learning
techniques to aid medical decision using available health databases such as PMSI (Programme de
Médicalisation des Systèmes d'Information, national database of hospital stays in France), SNIIRAM
(Système national d'information inter-régimes de l'Assurance maladie, national database of the health
insurance) and local databases of the CLB (Centre Léon Bérard, hospital specialized in cancer treatment
in Lyon, France). In a previous work (Prodel 2017), the application of classification methods such as
decision trees or random forest have proven very effective to predict the clinical pathway of patients
using a set of medical features. The same approach can be applied to the prediction of medical acts
within a hospital stay, for example: “Depending on his/her medical history, can an obese patient having
a severe heart condition have a heart surgery to implant a defibrillator?” or “Depending on the stage
of the lung cancer, what is the treatment among chemotherapy, radiotherapy and surgery that
optimize the survival rate of the patient?” This problem is partly related to the tuning of parameters
used to build decision trees (Camilleri et al. 2014; Coroiu 2016).

Particle swarm optimization techniques for feature selection, coupled with an optimization-based
discriminant analysis model (DAMIP) is an emergent and promising field of research when applied to
identify a classification rule with relatively small subsets of discriminatory factors that can be used to
predict resource needs, outcome for treatment... For example, (Lee et al. 2012) proposed a clinical
decision tool for predicting patient care characteristics and demonstrated that optimization achieve
better result than classical machine learning techniques. Such approach was also used for modeling
and optimizing clinic workflow (Lee et al. 2016).The scientific challenge of this thesis is twofold:
- Propose a theoretical research to develop new algorithms combining optimization and
classification methods applied to medical decision making, taking into account the special
features of the diagnosis related groups in France and in Europe. To do so, we will capitalize
on the short advance the I4S laboratory have on (i) research in the application of optimization
to predict patient clinical pathways by combining data/process mining, operational research
and machine learning and (ii) knowledge of health-care databases in France and in UK (through
the emerging collaboration with NHS and Westminster University, London, UK).
- Develop a comprehensive testbed experiment to assess the proposed algorithms on a lung
cancer case study. Several level of discovery will be used: hospital databases (PMSI), health
insurance databases (PMSI+SNIIRAM) and finally hospital databases (PMSI+SNIIRAM+Centre
Léon Bérard database) to understand the amount of required data needed to aid the medical
decision. To the best of our knowledge such case study has never been investigated in the
literature.

National databases such as PMSI and SNIIRAM are already available for such study, and a collaboration
with the Centre Léon Bérard (Lyon, France) is already live to access more detailed data, with the
support of the I-Care cluster (Lyon, France) for dissemination of ongoing research on big data and
healthcare.

Profile
The candidate should have strong background in data science (machine learning, process mining, data
mining, artificial intelligence), industrial engineering (formal modelling, flow simulation, performance
evaluation), operational research (mathematic modelling, optimization) and computer science (coding
C/C++/Python, Java, knowledge on mathematical libraries, statistics, optimization).
Send a CV, motivation letter, marks of the 3 previous years (including current one) to augusto@emse.fr
in order to schedule an interview.

References
(Camilleri et al. 2014) M. Camilleri, F. Neri, and M. Papoutsidakis. “An algorithmic approach to parameter selection in machine learning using meta-optimization techniques”. WSEAS Transactions on Systems, 13:202–213, 2014.
(Coroiu 2016) A. M. Coroiu. “Tuning model parameters through a genetic algorithm approach.” In IEEE
12 th International Conference on Intelligent Computer Communication and Processing (ICCP), pages
135–140, Sept 2016.
(Lee et al. 2012) Lee EK, F Yuan, DA Hirsh, MD Mallory and HK Simon. “A clinical decision tool for
predicting patient care characteristics: patients returning within 72 hours in the emergency department”, AMIA Annu Symp Proc., 495-504, 2012
(Lee et al. 2016) Lee EK et al. “Systems Analytics: Modeling and Optimizing Clinic Workflow and Patient
Care”, In Healthcare Analytics: From Data to Knowledge to Healthcare Improvement, chapter 9, 2016
(Prodel 2017) M. Prodel. “Process discovery and simulation of clinical pathways using health-care
databases”. PhD Thesis, 2017.
(van der Aalst 2004) Wil M van der Aalst. “Workflow mining: Discovering process models from event
logs”. Computers in industry, 16:1128–1142, 2004.

Ecole de Mines de Saint-Etienne France Go Academia
30 Jun 2017 Positions for assistant or associate professor in Computer Science

Toggle description

The Centro de Investigacion y de Estudios Avanzados (Center for Research and
Advanced Studies, Cinvestav after its name in Spanish), which is the top
public research center in Mexico, has two positions for full-time
researchers in Computer
Science to be filled for the Computer Science Department located at Mexico
City.

Candidates are required to have a PhD in Computer Science (or a related
field) and an outstanding research record, or a very good potential to
develop an outstanding
research career. Candidates from all areas of computer science are welcome
to apply.

Both junior and senior researchers are encouraged to apply for a position.
The type of appointment in turn could be as an Assistant or as an Associate
Professor.
The salary is competitive and varies depending on the curriculum of the
candidate (note that research experience is emphasized over teaching
experience).

The candidate is expected to have a light teaching load (one graduate-level
class per term), so that he/she can concentrate mostly on research
activities. Candidates do not need to be fluent in Spanish, as they can
teach in English.

CINVESTAV-IPN is the most important public research center in Mexico, with
645 full-time researchers and the second highest scientific productivity
(per researcher) of the country
(only after UNAM, which is the largest university in Mexico). The Computer
Science
Department offers both a MSc and a PhD program in Computer Science
(CINVESTAV-IPN only offers graduate programs). Both programs are included
in the National Graduate Program certification from CONACyT, which means
that all our Mexican full-time students receive
a stipend scholarship from the Federal Government (no tuition is required
for Mexican students).

The Computer Science Department of CINVESTAV-IPN currently has 17 full-time
researchers
and about 70 graduate students, and has research projects on Computer
architecture, Cooperative work, Cryptography, Databases, Evolutionary
computation, Optimization, Super computing and Visualization.


Interested candidates must send (via email to: jobs2013@cs.cinvestav.mx)
the following
information (as a single PDF file):

1) A detailed curriculum vitae that clearly indicates the publications in
international journals (highlighting the papers in journals included in the
Journal Citations Report), and a list of MSc and PhD graduates (if any).
The candidate should also include a copy of the three papers that he/she
considers as the most representative of his/her research. Note that papers
published in the Lecture Notes series from Springer will not be considered
as JCR papers.

2) A research statement that briefly (no more than 1 page) describes the
sort of research that the candidate has done so far and his/her research
plan in case of being hired.

3) A teaching statement that briefly (no more than 1 page) describes the
sort of graduate-level courses (in computer science) that the candidate can
teach (and has taught in the past, in case of having teaching experience).

4) The names and contact information (postal address, phone and fax number,
and email) of 3 references.

The screening of candidates will start at the end of June and the position
is expected to be filled by the end of 2017.

For further information, please contact:

Dr. Francisco Rodriguez-Henriquez
Chair, Computer Science Department
CINVESTAV-IPN
Av. IPN No. 2508
Col. San Pedro Zacatenco.
07300 Mexico City
MEXICO
Tel: +52 (55) 5747 3800 x 6564
Fax: +52 (55) 5747 3757
URL: http://www.cs.cinvestav.mx
email: francisco@cs.cinvestav.mx

CINESTAV Mexico Go Academia
30 Jun 2017 Tenure-track Assistant Professorship in Big Data Analytics

Toggle description

The Department of Informatics of the Faculty of Science at the University of Mons (Mons, Belgium) invites applications for a tenure-track faculty position in computer science, with special emphasis on big data analytics. The position is at the level of «chargé de cours» (assistant professor). The expected starting date for the position is October 1, 2018. Qualified candidates must have a doctorate in disciplines related to computer science or computer engineering, and should have a strong commitment to teaching and an outstanding research record in applied aspects of big data analytics. The selected person should collaborate with existing research groups of the department and be active in fundraising for industrial and governmental projects.

Candidates should be able to fulfil teaching duties in the French language after two years. Teaching duties are on both the undergraduate and graduate level, and include novel courses in the candidate’s domain of expertise.

The University of Mons is a university located in the French community of Belgium with about 8000 students. Information about the Department of Informatics can be found at http://informatique.umons.ac.be/.

Applications should be sent by email to Prof. Dr. Véronique Bruyère (veronique.bruyere@umons.ac.be), Department Head. We encourage candidates to apply from now on. Applications must be submitted as PDF files, which include a cover letter, curriculum vitae, a one-page statement of teaching interests, a one-page statement of research interests in big data analytics, and names and contact information of at least three references. Following their application, candidates will be informed in due time about the further application procedure.

The most up to date information about the position and the application procedure will be maintained at http://informatique.umons.ac.be/job_offers/.

Uniersity of Mons Belgium Go Academia
30 Jun 2017 Master Programme in OR and Combinatorial Optimisation

Toggle description

The Master Program in Operations Research, Combinatorics and Optimization is one of the possible specializations for the second year of the Master of Science in Computer Science (semesters 3 and 4). The courses are taught in English.

Scientific objectives:
•Study of advanced and efficient methods and tools of Operations Research, Combinatorics and Optimization (Mathematical programming, Graph theory, Complexity theory, Stochastic programming, heuristics, approximation algorithms, Robust optimization...)
•Emphasis is on the use of these methods to implement efficient solution techniques to complex industrial applications (in supply chain management, scheduling, transport …)
•Preparation for research positions (in industry and academia)

Professional objectives:
At the end of the program, the students should be able to pursue a career in research (academic or industrial PhD), or to join major research and development departments or consulting companies in optimization. They might also build upon their ability to analyze operational problems methodologically to join less specialized companies and act as key actors in performance management: either by interfacing with consulting firms or by developing in-house solutions. In the long run, students who are moving towards industrial careers, strengthened by their experience in improving business performances and by the development of business-specific knowledge, should naturally reach decision-making positions with a high level of responsibility

Grenoble University France Go Academia
13 Jun 2017 Phd or Postdoc position in Operational Research and Logistics

Toggle description

Applications are invited for aPostdoctoral Researcheror aPhD studentat the Department of Production and Logistics of the University of Wuppertal, Germany. The position is full-time and can be started as soon as possible for the applicant. The position is funded for three years (salary according to level E13).
We have a research focus on operations research methods with application in logistics, production planning and supply chain management. Applicants should have a business administration and/or theoretical/mathematical background and an interest in at least one of the following topics:
- operational research
- auction theory
- computational complexity theory
- scheduling theory
Postdoctoral researchers from other fields may apply as well, but should be prepared to detail how they fit in the research profile of the group.
All applicants should have an excellent first academic degree in computer science, mathematics, business administration or a related discipline.
Applications should include a detailed CV, a copy of master (or PhD) thesis, a brief statement of research interests, and a list of publications (if applicable).
Please send the application not later than June 13th, 2017 to

Bergische Universität Wuppertal,

Fakultät für Wirtschaftswissenschaft - Schumpeter School of Business and Economics,

Lehrstuhl für Produktion und Logistik,

Herrn Prof. Dr. Dirk Briskorn, 42097 Wuppertal

and via email to briskorn@uni-wuppertal.de

University of Wuppertal Germany Go Academia
09 Jun 2017 PhD position in scheduling for healthcare

Toggle description

A PhD position is available at TU Berlin, in the fields of discrete and robust optimization, for a start at the earliest possible date. The project, entitled "Robust Optimization of Load Balancing in the Operating Theatre", will be under the supervision of Guillaume Sagnol at the COGA Group of the Technical University of Berlin.

* Working field:
Working in the ECMath Junior Research Group "Optimization under Uncertainty“ and the project
"Robust Optimization of Load Balancing in the Operating Theatre". Further own research in the field of discrete and
algorithmic mathematics.

* Requirements:
Successfully completed university degree (Master, Diplom or equivalent) in Mathematics, grades clearly
above average desired; deep knowledge in combinatorial optimization and/or optimization under uncertainty; strong
interest in mathematical research; experience in scientific programming (e.g. Matlab, python, julia,...)

We welcome highly motivated candidates to send their electronic application per email to sagnol@math.tu-berlin.de (deadline for the application: 09.06.2017).

For further information do not hesitate to contact Guillaume Sagnol.

Technical University of Berlin Germany Go Academia
05 Jun 2017 Assistant Professor in System, Control, Optimisation

Toggle description

Assistant Professor position in Systems, Control, and Optimization at IMT Lucca.

IMT School for Advanced Studies Lucca invites expressions of interest for an Assistant Professor position (“Type-A Ricercatore”) to carry out research in the areas of systems, control, and optimization. Research experience is expected in one of the following areas: control systems, numerical optimization, systems identification, machine learning. Research experience in model predictive control or convex optimization will be considered as a plus.

Candidates must have an excellent record of high-impact international publications and demonstrate enthusiasm for performing research. Activities include: research, tutorship and mentoring of PhD students, graduate teaching. The successful candidate will be part of the research unit Dynamical Systems, Control and Optimization (http://dysco.imtlucca.it/) at IMT Lucca.

The position is for 3 years, extendable for further 2 years. The indicative starting gross salary is EUR 34.898/year, net income may vary depending on income taxes, local taxes, retirement plan, health care deduction and tax exemptions. New employees who have worked in research-based positions abroad for the past two years may be eligible for a substantial tax rebate for the first three fiscal years of employment.

IMT School for Advanced Studies Lucca (http://www.imtlucca.it) is a public graduate school and research institute, ranked #1 among all public Italian universities for quality of research in the last national research evaluation. IMT is an interdisciplinary research environment, blending scientific competencies of management science, engineering, computer science, neuroscience, physics, and management of cultural heritage, striving to reach the fusion of theoretical comprehension and practical relevance in concrete applications. The working language at IMT Lucca is English.

IMT School for Advanced Studies Italy Go Academia
01 Jun 2017 Postdoc position in algorithms

Toggle description

One year research position at a postdoctoral level (with a possible one year extension) is available at Algorithms research group (http://www.uib.no/rg/algo/), University of Bergen, Norway.

The successful candidate will work on "Multivariate Algorithms: New domains and paradigms" project funded by the Norwegian Research Council and led by Fedor Fomin. The objective of the project is to develop new theory of multivariate algorithms as well as to apply the new theory to fundamental algorithm design paradigms.

Candidates are required to have completed (or being close to completion) a PhD in the area of theoretical computer science, discrete mathematics or a related discipline. A strong background in algorithms, complexity theory, and combinatorics is a plus.

This is a full time research position, no teaching is required. Starting salary is on grade 57 (code 1109/pay framework 24.1) in the Civil Service pay grade table which currently means roughly NOK 450K NOK gross
p.a., taxes should be at most 40%.

Preferred starting date: August-September 2017. The application deadline is June 01, 2017.

If you are applying, you are encourage to contact Fedor Fomin ( http://www.ii.uib.no/~fomin/ - fomin@ii.uib.no ) for more details and information.

University of Bergen Norway Go Academia
31 May 2017 Junior Research Group Leader position in Discrete Optimisation

Toggle description

The Faculty of Mathematics and Computer Science at the University of
Würzburg invites applications for the position of a

Leader of a Junior Research Group

starting October 1, 2017 (or as soon as possible thereafter) for a
maximum of 5 years. The research group consists of the leader, a
postdoc, and a PhD position (50%). Payment will be according to scale
E14 of the Collective Agreement for the Public Service of German Federal
States (TV-L). We are looking for an excellent young researcher from
one of the following two areas:

Discrete Optimization Strategies for Applications

or

Computational Sciences --
Algorithms for Applications in the Natural and Life Sciences
(efficient implementation of mathematical models from the
natural and life sciences on high-performance computers).

The research group is expected to strengthen the links between the
Institute of Mathematics and the Institute of Computer Science.
Experience with interdisciplinary research cooperations (e.g., in
biology, medicine, or physics) is a plus. The position comes with mild
teaching duties (5 contact hours per week) within the B.Sc. and M.Sc.
programs of the Faculty. The group leader is expected to hold a PhD (or
an equivalent degree) with very good grades, a strong publication
record, and experience in an international research environment.

Würzburg is a beautiful town in the wine region of Lower Franconia,
just 90 train minutes from Frankfurt airport. More than a quarter
of the 120,000 inhabitants of Würzburg are students. The University
and the Faculty of Mathematics and Computer Science have been growing
dynamically over the last few years, partially thanks to the Bavarian
digitalization initiative.

The junior research group is part of the "Excellent Ideas" program of
the University of Würzburg:
https://www.uni-wuerzburg.de/en/ueber/research/junior_research_groups/

The University of Würzburg is an equal opportunity employer. As such,
we explicitly encourage applications from women. Applications from
disabled persons with essentially the same qualifications will be given
preference.

Please submit your application by _May 31, 2017_ with the usual
documents (CV, certificates, list of publications, list of modules
taught) and a short research proposal (including state of the
art, potential research links to the Faculty and the University,
research plan, milestones) as pdf files via

https://go.uniwue.de/researchgroup-mi

Further information will be requested in the submission process.
Don't hesitate to contact the faculty manager:

Dr. Richard Greiner
email: greiner "at" mathematik.uni-wuerzburg.de
phone: +49 931 3185029

University of Wuerzburg Germany Go Academia
31 May 2017 PhD positions in various areas of computer science and optimisation

Toggle description

The Gran Sasso Science Institute (GSSI - http://www.gssi.it/ ), a recently established international PhD school and a Centre for advanced studies in L'Aquila (ITALY), offers 10 PhD positions in Computer Science (CS).

The PhD program in CS is mainly concerned with heterogeneous distributed systems and their interactions. Different perspectives are offered to provide students with the necessary tools for the design, the implementation, the management and the use of distributed systems. The main research areas of interest are:
- Efficient algorithms for communication networks and social networks;
- Formal methods for systems correctness and analysis;
- Software engineering for efficient and resilient applications.

Apart from pursuing their own research studies, the successful candidates will have the opportunity to cooperate with members of the research group and of the Scientific Board, as well as with the frequent guests of the Institute. Detailed information about the CS research group and about the activities for the PhD program in CS can be found at http://cs.gssi.it/

The fellowships are awarded for three years and their yearly amount is € 16.159,91 gross. Moreover all PhD students:
- will have free accommodation at the GSSI facilities and luncheon vouchers;
- will have tuition fees waived;
- will be covered by insurance against accident and/or injury.

The application must be submitted through the online form available at http://www.gssi.it/phd/ and must be accompanied by the curriculum vitae and by a letter of motivation describing expertise and general research interests together with future plans and reasons for having chosen GSSI for PhD studies.

The deadline for application is: 31st May 2017 at 18.00 (Italian time zone).

Gran Sasso Science Institute Italy Go Academia
31 May 2017 PhD Position in Optimisation of Planning Operations for End-of-Life Products

Toggle description

The research pursued by the PhD student will concern the development of new models and original solution methods for the optimization of planning operations for end-of-life products. It aims at addressing problems dealing with the newly introduced concept of circular economy and greenhouse gas emissions, recently raised by the French government. Companies are currently facing two antagonist objectives. On the one hand, they must ensure a local economic development that creates wealth; on the other hand, they must satisfy environmental constraints related to their production. In this challenging context, one of their major issues is to minimize the consumption and waste of raw materials while limiting the use of non-renewable energies.

Meanwhile, new communicating technologies could provide necessary traceability information about end-of-life products, their state and the state of their components. This information can help organizing and optimizing remanufacturing and disassembly processes. The process of valuing end-of-life products could be economically viable, and therefore valuable from an industrial point of view.

In the light of the above background, this thesis focuses on the use and advantage taking of new communicating technologies in remanufacturing and disassembly systems. The goal is to develop new models and original solution methods for planning remanufacturing and disassembly systems that exploit this new procured information, while satisfying both resource and environmental constraints. The proposed news approaches will be defined and tested with industrial partners.

Candidate profile: Applicants must have a Master Degree (or equivalent) in Computer Sciences, Applied Mathematics or any related discipline. Applicants should demonstrate good programming skills and a deep knowledge in combinatorial optimization and integer programming.

Location: The PhD student will be located in Gardanne (south of France, near Aix-en-Provence) in the research group Manufacturing Sciences and Logistics of the Georges Charpak Provence Campus of the Ecole des Mines de Saint-Etienne.

Duration and assumption of duty: The position is for three years starting September 1, 2017 (exact date is negotiable).

Application procedure: Please send your application electronically (preferably as a single pdf file) including a detailed curriculum vitae and examination results, plus, if available, a list of reference letters and copies of diploma, to: Nabil ABSI (absi@emse.fr) or Valeria BORODIN, (valeria.borodin@emse.fr). The position will remain open until fulfilled.

For further questions regarding the position or details on the research project, please contact Nabil ABSI or Valeria BORODIN.

Ecole de Mines de Saint-Etienne France Go Academia
30 May 2017 Assistant Professor (tenure track) in algorithms and optimisation

Toggle description

Tenure-track Assistant Professor in Algorithms and Optimisation
Department of Computer Science
University of Copenhagen

The position is open from 1 November 2017 or as soon as possible thereafter.

The Department of Computer Science (DIKU) is expanding its research and
educational activities and hereby invites applications for a *tenure-track
assistant professor in Algorithms and Optimisation*. The tenure-track
assistant professor will join the department’s Algorithms and Programming
Languages Section (http://www.diku.dk/english/research/apl-group/). The
section’s research is concerned with a wide range of areas related to
algorithms, programming languages and systems. In the area of algorithms,
our research covers discrete optimization algorithms and theoretical
aspects of algorithms and data structures.

The candidate must have a strong background in at least one of the
following two sub-fields:

- Applications of discrete (optimization) algorithms and data structures
to problems in for example bioinformatics, network design, logistics.
Candidates with publications at top bioinformatics, operations research
conferences and journals will be preferred.
- Theoretical aspects of algorithms and data structures. Candidates with
publications at top algorithms/theory conferences such as STOC, FOCS, SODA,
ICALP will be preferred.Read more about the Department at
http://www.science.ku.dk/english/about-the-faculty/organisation/.

Please find the full job advertisement at http://employment.ku.dk/.

Only electronic applications are accepted.

University of Copenhagen Denmark Go Academia
30 May 2017 PhD positions in optimisation of semiconductor manufacturing

Toggle description

Two PhD positions (one industrial and one more academic within a European project) are available at the Ecole des Mines de Saint-Etienne (Gardanne, France) on semiconductor manufacturing related problems within
projects in cooperation with STMicroelectronics (in Rousset and in Crolles), one of the worldwide leaders, and other partners.

The two topics are summarized below.
***************************************************************************
1. Industrial PhD thesis (CIFRE) With STMicroelectronics in Crolles (France, 38).
Title : "Robust Management of Product Qualifications in Industry 4.0"
Short abstract: The objective of the thesis is to develop methodologies and decision-support tools to deal with the low visibility and high variability of product demands. The configuration of the machines in the various production workshops is now managed according to a short-term load plan. Nevertheless, recent events (sudden and unexpected peaks) have clearly demonstrated the need to develop a consistent approach for the qualification of machines. This thesis aims at developing a static approach proposed by the EMSE, integrating the anticipation and robustness aspects of demand forecasting. A method and a tool should be proposed for the management of qualifications in all the workshops of Crolles300.

The PhD thesis should include robust and stochastic discrete optimization.
***************************************************************************
2. PhD thesis within the European PRODUCTIVE 4.0 in Gardanne (France, 13).
Title: "Novel optimization approaches for global fab scheduling"
Short abstract: The fabrication of semiconductor devices is probably the industrial process with the most complex process flows from wafer fabrication through test and then assembly. To optimize the agility of semiconductor manufacturing facilities and move toward “Industry 4.0”, new approaches should be developed and implemented. Within the European project PRODUCTIVE 4.0, the objective of this thesis on "Global fab scheduling" is to develop an approach using analytical and simulation models to ensure consistency between fab production control and scheduling at workshop level. The notion of of “yield criticality” at product/step level will be integrated together with equipment health, performance or risk criteria. A global factory simulation model including models at lower (tool and workshop) levels will be studied. Varying mix and toolset configurations and varying WIP (Work-In-Process) management strategies will be considered and evaluated. The approach will be validated on industrial data.

This thesis will be part of a large European project with multiple industrial partners, including Infineon and STMicroelectronics. It will include large-scale optimization, in combination with a simulation model already developed but that could be extended.
***************************************************************************
The PhD theses will be conducted in cooperation with the research group "Manufacturing Sciences and Logistics" of the Center of Microelectronics in Provence (Ecole des Mines de Saint-Etienne), located in Gardanne (South-East of France, between Aix-en-Provence and Marseille).

The PhD students will be located either in the site of Crolles (close to Grenoble) of STMicroelectronics for the first topic and in Gardanne for the second topic.

The positions are for three years and can start as early as June 2017 (exact date to be discussed).

Applicants must have a Master Degree (or equivalent) in Computer Sciences, Applied Mathematics, Industrial Engineering or any related discipline. Applicants should demonstrate good programming skills and knowledge in combinatorial optimization. Experience on the development of solution methods for planning or scheduling problems or/and in simulation would be appreciated

Please send your application electronically (preferably as a single pdf file) including a detailed curriculum vitae and examination results, plus, if available, a list of reference letters and copies of diploma, to: Professor Stéphane Dauzère-Pérès,dauzere-peres@emse.fr.

For further questions regarding the positions or details on the research projects, please contact Stéphane Dauzère-Pérès

Ecole de Mines de Saint-Etienne France Go Academia
29 May 2017 Pre/post-doc position in Mixed Integer Nonlinear Programming

Toggle description

Cari Colleghi,

desidero segnalare la pubblicazione di un bando (scadenza 29.05.2017) per un assegno di ricerca (durata totale 17 mesi) presso il dipartimento di Matematica dell'Università di Padova:

Bando n. 6/2017
Titolo: "Mixed Integer Nonlinear Programming: Relaxation and Constraint Enforcement"

Gli interessati possono contattarmi al seguente indirizzo: rinaldi@math.unipd.it

University of Padova Italy Go Academia
17 May 2017 PostDoc position in optimization of an advanced manufacturing system

Toggle description

The Operations Research Group of the University of Milan (Italy),
opens one PostDoc position on the modelling and optimization of an advanced
manufacturing system for the production of architectural windows and doors.

This position is supported by a grant issued by Regione Lombardia
and its aim is technology transfer to the industrial partner of the project.

The appointment is for 18 months, with a gross salary of 20.800 EUR per
year,
roughly corresponding to 1.500 EUR per month.

The ideal candidate should hold at least a Master's Degree (preferably,
a Ph.D.)
in Computer Science, Engineering, Mathematics or Physics and a good
expertise
in the development of mathematical programming models, in the C/C++
implementation
of exact and heuristic algorithms and in the use of general-purpose
software
for optimization.

The call for applications, in Italian, can be found at:
http://www.unimi.it/ricerca/assegni_ricerca/109684.htm
An English translation is available on request.

The closing date for applications is the 17th May 2017.

For any question, and in particular to prepare a possible application,
please contact:

Prof. Roberto Cordone
roberto.cordone@unimi.it
http://homes.di.unimi.it/cordone/

University of Milan Italy Go Academia
15 May 2017 Assistant Professor positions in Data Science and AI

Toggle description

The Department of Data Science and Knowledge Engineering (DKE) at Maastricht University invites applications for five full-time assistant professor positions in the following fields: Cybersecurity, Deep Learning, Advanced Statistics, Data Visualization, Image Processing.
Applications received by May 15th, 2017 will receive full consideration. The positions will remain open until filled. Applicants may be called in for an interview.
It is intended to fill these positons as soon as possible.
For more information on these positions: https://lnkd.in/gTXrWpK
For more information on the department: https://www.maastrichtuniversity.nl/dke

Maastricht University Netherlands Go Academia
15 May 2017 Postdoc position in approximation algorithms

Toggle description

The Algorithms and Complexity Group of IDSIA, University of Lugano
(Switzerland), opens one PostDoc position in approximation algorithms.
This position is supported by the
Swiss National Foundation Grant "Approximation Algorithms for Network Problems".

The appointment is for one year, with tentative starting date on 1st
November 2017.
The gross salary is roughly 80.000 CHF per year (low taxes, around 15%).
There are no teaching duties and there is generous travel support.
The ideal candidate should hold (or be close to obtaining) a Ph.D. in
Computer Science, and should have a solid
publication record in the area of algorithms and complexity (possibly
in approximation algorithms). Top conferences in this area include
STOC, FOCS, SODA, ICALP, and ESA.

Team members will have the opportunity to cooperate with the
Algorithms and Complexity group at IDSIA, which currently counts 7
researchers. The current research interests of the group include:
- network design;
- resource allocation and scheduling problems;
- geometric packing problems;
- "fast" approximation algorithms.

IDSIA offers an international working environment. Lugano is a tidy
and lively town, with a wonderful view on Ceresio lake and mountains
around. Ticino Canton offers many opportunities for hiking, biking,
skiing, etc. Local restaurants serve very good (Italian style!) food.

Further details about the project can be found at:
http://people.idsia.ch/~grandoni/SNF2015.html

The interested candidates should email
- a detailed CV, including a list of publications and 2-3 references, and
- a short summary of past and current research interests
to:
fabrizio@idsia.ch

Applications should be sent as soon as possible, and in any case no
later than May 15th, 2017.
For any question, do not hesitate to contact:

Prof. Fabrizio Grandoni
fabrizio@idsia.ch
http://people.idsia.ch/~grandoni/

University of Lugano Switzerland Go Academia
12 May 2017 PhD position in Operational Research

Toggle description

PhD Thesis opportunity at Le Havre Normandy University.

Title: Optimization problems in temporal networks
Supervisors: Yoann Pigne, Eric Sanlaville
Keywords: graphs, optimization algorithms, temporal networks, dynamic graphs
Funding source: Public funds (French Ministry of Education and Research)
Deadline: Friday 12th of Mai, 2017

A temporal network, also called dynamic graph, is a graph defined on a time interval, where arcs (resp. vertices) might not be present at any time, but only occasionally [1]. Temporal networks allow to represent nodes and arcs presence variability in ad hoc mobile networks or social networks, as well as transportation networks submitted to traffic congestion. Hence they are a very interesting model for communication and logistic problems. [2], [3].

Our goal is to study some classical optimization problems on graphs within this new framework. Moreover, as the formalism for these networks is not completely fixed in the literature, a part of the work will consist in proposing the best adapted one for the tackled problems [4]. Determining for instance flows, particular structures like connected components valid during the considered time interval, will be considered. Several solving approaches like meta-heuristics, mathematical programming, approximation algorithms, will be exploited according to the treated problem natures.

The thesis subject fits well the research themes of the RIIC team (Interaction Networks and Collective Intelligence) of the computer science research department LITIS. Indeed, dynamic graphs are the backbone of the team work. The in-depth analysis of optimization methods in temporal networks will find immediate applications in the applied research funded projects of the team (logistics [3],[6], mobile networks [7], load balancing [8]). Indeed, temporal networks allow to model and control the evolution with time of this kind of physical networks.

The RI2C team develops a software platform to manipulate dynamic graphs, GraphStream [9], [10], this work will enrich the software by the way of a new model to represent and analyse dynamic graphs.

Work plan:
* Analysis of the temporal networks models from the literature.
* Extension of optimization problems to temporal networks
* Design, analysis of solving algorithms for these problems
* Implementation of the algorithms and models within GraphStream
* Scientific valorization
* Thesis writing

The chosen candidate shall display strong skills in graph theory and optimization. An excellent technical level in software development is expected (particularly in Java). The Software engineering basis techniquesmust be mastered and used (test oriented development, version management). He/She will organize his/her work and be able to respect the fixed due dates. Skills in statistic analysis and the knowledge of R language would be appreciated.

Interested candidates should send by mail CV, motivation letter and any additional material (master marks, training reports, recommendation letters,GitHub profile,...) to Eric Sanlaville (eric.sanlaville@univ-lehavre.fr) and Yoann Pigné (yoann.pigne@univ-lehavre.fr).

[1] P. Holme et J. Saramäki, « Temporal networks », /Physics Reports/, vol. 519, no 3, p. 97-125, oct. 2012.
[2] B. B. Xuan, A. Ferreira, et A. Jarry, « Evolving graphs and least cost journeys in dynamic networks », présenté à /WiOpt’03: Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks/, 2003, 10 pages.
[3] F. Guinand et Y. Pigné, « Time considerations for the study of complex maritime networks », in /Maritime Networks Spatial structures and time dynamics/, César Ducruet, Routledge, 2015, p. 163-189.
[4] D. Kempe, J. Kleinberg, et A. Kumar, « Connectivity and Inference Problems for Temporal Networks », in /Proceedings of the Thirty-second Annual ACM Symposium on Theory of Computing/, New York, NY, USA, 2000, p. 504–513.
[5] O. Michail, « An Introduction to Temporal Graphs: An Algorithmic Perspective », /Internet Mathematics/, vol. 12, no 4, p. 239-280, juill. 2016.
[6] S. Balev, S. Michel, E. Sanlaville, et X. Schepler, « Global planning in a multi-terminal and multi-modal maritime container port », /Transportation Research Part E/, accepté, déc. 2016.
[7] A. Casteigts, S. Chaumette, F. Guinand, et Y. Pigné, « Distributed maintenance of anytime available spanning trees in dynamic networks », in /International Conference on Ad-Hoc Networks and Wireless/, 2013, p. 99–110.
[8] J. L. J. Laredo, F. Guinand, D. Olivier, et P. Bouvry, « Load Balancing at the Edge of Chaos: How Self-Organized Criticality Can Lead to Energy-Efficient Computing », /IEEE Transactions on Parallel and Distributed Systems/, 2016.
[9] A. Dutot, F. Guinand, D. Olivier, et Y. Pigné, « Graphstream: A tool for bridging the gap between complex systems and dynamic graphs », in /Emergent Properties in Natural and Artificial Complex Systems. Satellite Conference within the 4th European Conference on Complex Systems (ECCS’2007)/, 2007.
[10] « GraphStream - A Dynamic Graph Library ». [En ligne]. Disponible sur: http://graphstream-project.org/. [Consulté le: 06-févr-2017].

Le Havre Normandy University France Go Academia
11 May 2017 Assistant Professor position in Computer Science / Structural Combinatorics

Toggle description

Applications are invited for a 3-year position as Assistant Professor in Computer Science with specialization in Structural Combinatorics at the Department of Applied Mathematics (KAM), Faculty of Mathematics and Physics, Charles University in Prague, Czech Republic, with the possibility of renewal and shift to tenure track.

Candidates should have a PhD in Mathematics, Computer Science or Operations Research, and demonstrate strong potential for excellence in research.

The successful candidate will be expected to conduct research related to structural combinatorics, graph theory, design and analysis of algorithms.

The successful applicant will teach in English and within three years also in Czech, topics mainly from discrete mathematics and computer science. Good knowledge of Czech is advantageous but not necessary.

Desirable are a previous postdoc in combinatorics and strong background in graph theory and computer science.

Signed application in digital form, accompanied by a motivation letter, curriculum vitae, proof of education, list of publications, and a description of pedagogical experience should be sent to the Department of human resources jancak@dekanat.mff.cuni.cz
by May 11, 2017. The candidates should also arrange for two recommendation letters to be sent electronically to
Martin Loebl (head of KAM) loebl@kam.mff.cuni.cz
Selected candidates will be invited for interview in May.

Charles University of Prague Czech Republic Go Academia