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Here is an opening for a research fellow position in Pisa, concerned with mixed-integer non-linear programming (MINLP) problems.

To apply, follow the instructions at this link:

https://www.unipi.it/ateneo/bandi/assegni/2019/inf/07112019/index.htm

Deadline: 7 November 2019, 13:00 (Rome, Italy time)

About the research:

We are looking for an enthusiastic research fellow to join us, studying mathematical optimization problems that combine both discrete and (continuous) nonlinear elements.
It is well-known that the algorithmic approaches for Mixed-Integer Linear Programming (MILP) and Non-Linear (continuous) Programming (NLP) taken alone
are not sufficient to tackle this class of problems. Indeed, the underlying mathematical structure combines non-convexities of the discrete elements with nonlinear functions.
This is very significant from a practical point of view, in that it allows to more accurately model the complex structures that are required by real applications, ranging from energy, telecommunication to transportation and logistics, fostering an interplay between industry and academia.
Currently, there are several theoretical, algorithmic and computational challenges in MINLP, that have now clearly caught the attention of all major optimization societies.

The position is funded for 2 years.
Please circulate to potentially interested people.

Contact:
Laura Galli
Senior Assistant Professor of Optimisation
Department of Computer Science
University of Pisa
Largo B. Pontecorvo, 3
56127, Pisa
T: +39 (0)50 2212715

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The University of Exeter’s College of Engineering, Mathematics and Physical Sciences is inviting applications for a fully-funded PhD studentship to commence in February 2020 or as soon as possible thereafter. For eligible students the studentship will cover UK/EU/International tuition fees plus an annual tax-free stipend of at least £15,009 for 3.5 years full-time, or pro rata for part-time study. The student would be based in the College of Engineering, Mathematics and Physical Sciences at the Streatham Campus in Exeter.

Project Description:
Mathematical optimisation problems arising from real-world applications typically consist of many interconnecting components, i.e. a fleet of vehicles at a delivery depot, crew and aircraft in airline operations and the numerous, semi-autonomous power stations supplying the electricity grid. These interconnections introduce structure that can be exploited through the use of decomposition techniques. A popular decomposition technique used to exploit such structure is Benders’ decomposition.

Recently, a general Benders’ decomposition framework has been made available within the mathematical and constraint programming solver SCIP (scip.zib.de). This framework provides the functionality to solve many real-world optimisation problems, specifically mixed integer programs and convex quadratic programs. However, there are still many problem classes that are not fully supported, such as convex and non-convex mixed integer non-linear problems. The goal of this project is to extend the Benders’ decomposition framework in SCIP to handle a wider range of problem classes. This will involve the development of novel solution algorithms that can be applied to general problems instances.

This project requires a high competency in mathematics and software design and development. You will become part of the SCIP Development Team (scip.zib.de) and contribute to the growth of this highly regarded general purpose solver. Knowledge of discrete optimisation, operations research and linear programming is a bonus.

How to apply:
In the application process you will be asked to upload several documents.
• CV
• Letter of application (outlining your academic interests, prior research experience and reasons for wishing to undertake the project).
• Transcript(s) giving full details of subjects studied and grades/marks obtained (this should be an interim transcript if you are still studying)
• Two references from referees familiar with your academic work. If your referees prefer, they can email the reference direct to stemm-pgr-admissions@exeter.ac.uk quoting the studentship reference number.
• If you are not a national of a majority English-speaking country you will need to submit evidence of your proficiency in English.

The closing date for applications is midnight on 1st November 2019. Interviews will be held on the University of Exeter Streatham Campus the week commencing 18th November 2019.

If you have any general enquiries about the application process please email stemm-pgr-admissions@exeter.ac.uk or phone +44 (0)1392 722730 or +44 (0)1392 725150. Project-specific queries should be directed to Dr Stephen J. Maher s.j.maher@exeter.ac.uk.

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We are looking for a highly motivated candidate for a PhD in operations research and data science. The PhD is in collaboration with Padam (www.padam.io), a company working on a turnkey platform and developing simulation tools for on-demand transportation systems.


At the interface of 2 hot and trend topics, the project will be oriented on the following aspects:

- The design of exact and heuristics algorithms for routing problems to efficiently tackle instance of the company

- The use of original data science and probabilistic methods to improve routing decisions


To achieve this goal, the candidate will have to suggest novel algorithms combining advanced optimization techniques (e.g. mathematical programming models, hyper- and meta- heuristics) with robust and data-driven optimization techniques.


Applicants should have (or be about to finish) a relevant master degree. Good knowledge of operations research techniques (integer linear programming, graphs etc.) and data science/machine learning tools are strongly recommended. The applicant should also have good programming skills in any programming language. Expertise in working with a unix-like system (e.g. ubuntu) and knowledge in database models will be appreciated.


The PhD thesis will take place in 2 locations:
- Paris XIII University - 99, av. Jean-Baptiste Clément - 93430 Villetaneuse
- Padam - 34 boulevard Sebastopol - 75001 Paris

For more information contact:
Emiliano Traversi traversi@lipn.univ-paris13.fr
Roberto Wolfler Calvo wolfler@lipn.univ-paris13.fr

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We are building the most intelligent pricing strategy in fashion industry.
Operating in more than 15 markets and having a complex logistics.

Our aim is to bring together the power of pricing and forecasting in-order to steer our sales and improve our customer experience in all markets.

The Zalando PhD Fellowship Program is designed to encourage and support promising PhD students who are engaged in innovative and relevant research in areas related to computer science and machine learning and in general artificial intelligence (AI) at an accredited university.

The program is open to students in any year of their PhD study and is flexible with respect to start and end dates of the internship.

Applications are evaluated based on the strength of the student’s research statement, publication record and their programming skills.

We accept applicants from around the world.


RESEARCH AREAS

Optimization layer within a neural network
Multi-task learning
Graph learning
Reinforcement learning
Directly learning the gradient of a function from data
PDE based time-series forecaster


WHERE YOUR EXPERTISE IS NEEDED

Apply state of the art deep learning methods such as having an optimization layer within the forecaster network
Multi-task learning with more than 400K tasks and graph learning to solve our real-world problems in pricing and forecasting
Graph learning to reveal article interactions
Apply technologies and tools proficiently to maximize output and efficiency
WHAT WE ARE LOOKING FOR

Senior PhD students with a strong background in mathematics
Fluent in Python programming
Knowledgeable about state of the art deep learning solutions and familiar with optimization algorithms
Proficiency in English


PERKS AT WORK


Acquire stakeholder management skills in a fast paced e-commerce environment
Large amount of data and one of the best ML infrastructure in Europe
Centrally located offices, municipality services, flexible working times, free beverages and fruits, diverse sports and health offerings
A workplace run on trust, empowerment and feedback; positive, inspiring working atmosphere
A full-time, paid internship for at least 4 months, starting ASAP



We celebrate diversity and are committed to building teams that represent a variety of backgrounds, perspectives and skills. All employment is decided on the basis of qualifications, merit and business need.


ABOUT ZALANDO

Zalando is Europe’s leading online platform for fashion, connecting customers, brands and partners across 17 markets. We drive digital solutions for fashion, logistics, advertising and research, bringing head-to-toe fashion to more than 23 million active customers through diverse skill-sets, interests and languages our teams choose to use.

Job Info:
Location: Berlin
Contract: Internship
Job Category: More Central & Business Roles
Experience Level: Internship / Working Students
Reports to: Principal Data Scientist
Team Size: 5-10
Contact Recruiter Joanna Litwin - E-Mail: joanna.litwin@zalando.de

Please note that all applications must be completed using the online form - we do not accept applications via e-mail.

Link: https://jobs.zalando.com/en/jobs/1821624/?gh_jid=1821624&gh_src=mae4u01

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Description:
The Department of Management at Università Ca' Foscari Venezia invites applications for n. 1 fellowships in ‘Big Data Analytics Techniques for intangible assets analysis’, INTERREG V A IT- HR CBC Programme - "Standard" - Project: "Smart strategies for sustainable tourism in LIvely cultural DEstinations, S.LI.DES." (Project ID: 10044622) - CUP H74I18000060006 – under the supervision of prof. Raffaele Pesenti SSD MAT/09.
The research may be carried out in Italian and English.
The fellowship is intended to provide the successful candidate with the opportunity to pursue his/her own research while benefiting from the range of expertise at Università Ca' Foscari Venezia.

Position’s Identification code:
Title: Big Data Analytics Techniques for intangible assets analysis
WP3, A3.1, A3.2, A3.4, WP4, A4.2, WP5, A5.1
Abstract: Many heritage cities currently suffer damaging anthropic pressure on local cultural heritage. There is growing need to support the development of sustainable tourism practices, through the availability of dynamic and specific knowledge on visitor flows and local economic activities in order to better distribute the tourism demand in time and space. The research project aims to study and develop models and methodologies to analyze, monitor and manage visitor flows and mobility patterns in congested cities in order to decrease human pressure to heritage sites to preserve and valorize local identity and (tangible and intangible) typical cultural heritage. The research activity will be particularly focused on developing now-casting/forecasting models and scenarios and possibly also on data analysis, interactive datahub & dashboard design, dynamic mapping. The research activity also involves collaborating with various local stakeholders in order to highlight problems, identify approaches and validate solutions. Consequently, missions in Italy and abroad may be required to interact with the subjects. It is also necessary that the research fellow guarantees the presence, quantifiable in at least two days a week, in the Department.

Who can apply:
Prospective candidates are expected to hold master’s degree in computer science; statistics; math; physics; computer science/IT; automation; systemics and mathematical modelling, o electronics; economics and management and relevant experience on the research topic and scientific-professional curriculum suitable to the development of research activities related to the fellowship.
Ca' Foscari encourages applications from researchers with positive evaluation in all the criteria in individual proposals such as Marie Skłodowska Curie Actions - Individual Fellowships/ERC Starting Grants/FIRB (Italian Fund for basic research investments)/SIR (Scientific Young Independence Research) or similar.
Researchers having successfully completed Marie Skłodowska Curie Actions - Individual Fellowships/ERC Starting Grants/FIRB (Italian Fund for basic research investments)/SIR (Scientific Young Independence Research) or similar funded projects are warmly encouraged to apply.

Duration of contract: 12 months (approximately starting: November 2019);

Stipend: The research fellowship amounts to 19.367,00 Euros per year, including taxes and social
charges.

Deadline for submission of applications: October 25th 2019, 12 noon (Italian time).

How to apply:
see related link.

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Vattenfall aims to be Fossil free within one generation. A significant part of that journey is to develop, build and operate our Offshore Windfarms. With an increased competition on the market, increasing number of won projects and a larger asset portfolio the capability to design the world’s most efficient future wind farms is essential.

Vattenfall has also started a successful journey into digitalization and usage of analytics for business decisions. Our efforts in using Operational Research and Analytics for offshore wind farm design has been recognized by international awards, proving our to be state-of-the-art work in the applications of these techniques in practice.

In this framework, we are looking for a Optimization Specialist with Operational Research experience to grow our modelling team within the System Design department.

• Do you thrive in a true engineering environment with high technical focus and great ambitions?
• Will development and usage of mathematical optimization to answer complex questions motivate you?
• Are you motivated to solve complex real-world optimization problems that can contribute to a fossil free future?
• Do you want to work with some of the absolute best in the field?
• Would you take the challenge of working on the latest challenges of this quickly developing field?
• Are you ready for accelerated learning?
• Would you like to take part in developing a greener future?
• Would you like to work with a holistic mindset while having eyes for the details?

Then this is a great opportunity for you.

You will be part of the modelling team within System Design department which is the competence center for evaluation and modelling of technical solutions across the entire wind farm design. We use operations research and analytics for optimizing various aspects of the design, construction, and operation of our wind farms. Given the results we have achieved so far we want to accelerate the use of mathematical optimization in our business by creating a group with a strong OR expertise, that will be able to work on optimization tasks across the organization.

Your job

You will be part of the establishment of a strong Operations Research team in the energy business, working with the best specialists in the business. You will work closely together with experts and specialists in various departments inside the company, and be responsible for the development of optimization routines in Vattenfall. You will interact with different stakeholders, translating their specific needs into problems which can be solved using advanced mathematical optimization and analytics.

In particular, you will continuously create new and extend existing mathematical based optimization routines that integrates into the existing model suite we use to explore multiple potential solutions, and create robust pre-designs of wind farms, to guide our business decisions as well as making credible pre-evaluation of new technologies on product, system and park level. The achieved findings and recommendations are essential to guide Vattenfall’s technology planning and technology roadmaps in order to be able to develop, construct and operate the most cost efficient windfarms in the world.

Main tasks includes:
• Develop optimization routines that integrate into a bigger model framework
• Participate in the exploration of new optimization challenges.
• Identify optimization needs inside the company and their potential.
• Proof and validate the results of the developed models/routine
• Maintain interfaces to the academic world and participate in various research projects
• Personal growth

Your profile

You have an innovative mind-set and can see yourself working in a department where we value entrepreneurship, the pragmatic approach and helpfulness in our daily work. You can work self-dependent while sharing and seeking knowledge inside and outside the team. You have experience handling a long-term optimization project and like working in group. You show initiative and have a flexible approach to your work. You possess good interpersonal skills and can communicate technical messages on a clear and constructive way both internally and to external partners. You thrive in an informal environment, where we often invent the process and tools. In addition, the following qualifications are important for this position:

• Our successful candidate has a PhD degree (or equal) in Operational Research or 3 year experience in working with Operational Research projects
• Experience in carrying out a project in autonomy
• Positive, motivated and able to speak with different stakeholders
• Good knowledge of coding for optimization (C, C#, python or similar) and optimization tools (CPLEX, Gurobi or similar)
• Experience with Vehicle Routing, planning problems, and/or large-scale problems is a plus
• Experience in optimization for the wind business is a plus
• A strong connection with international research teams from academia, is a plus.
• Strong analytical mind, that on one side can dig deep into advanced optimization methods and on the other side understands the business impact of the results, and sees the bigger picture.
• Sitting in the System design department, a profound system understanding with multiple parameters and interfaces, embracing high complexity, is paramount.
• Natural curiosity and strong personal drive to constantly challenge the perceived reality, and do your best to steer away from sub-optimal solutions.
• Strong command of English, both verbally and written.

We offer:

We offer a challenging and independent job in an informal working environment. Good remuneration, a challenging and international work environment, and the possibility to work with some of the absolute best in the field. You will be working in an interdisciplinary and international team and you can always count on support from committed colleagues. We offer attractive employment conditions and opportunities for personal and professional development.

Location:
Office location is Kolding, Denmark, but occasional travel within northern Europe shall be expected.

More information:
For more information about the recruitment process contact Jette Ingeberg, Senior Recruiter on +45 22 57 07 51.
For inquires relating to the job content and scope feel free to contact Thomas Hjort, Head of System Design on +45 27 87 49 07.

Application
We look forward to receiving your application in English, including CV and cover letter via the application button at this page. The application deadline is October 20th 2019, but we conduct interviews on an ongoing basis. Therefore we encourage you to apply as soon as possible.

We look forward to receiving your application.

Our Organization:
At Vattenfall we are convinced that diversity contributes to build a more profitable and attractive company and we strive to be a good role model regarding diversity. Vattenfall works actively for all employees to have the same opportunities and rights regardless of gender, ethnicity, age, transgender identity or expression, religion or other belief, disability or sexual orientation.

Energy is our contribution to quality of life – day after day. With around 20.000 colleagues Vattenfall provides comprehensive electricity and heating offerings to several million customers in northern Europe. For the work ahead we need people who are fully dedicated to our customers and to a sustainable society – people like you.

Business Area Wind is responsible for Vattenfall’s Onshore and Offshore Wind as well as other non-hydro Renewable activities like solar PV and batteries. Today we develop, construct and operate wind generation in Sweden, Denmark, Germany, the Netherlands and the UK. In addition, we have a clear strategy to develop our solar PV and battery operations further.

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Applications are invited for a postdoctoral position within the Machine Learning group at BCAM. The postdoctoral candidate will work under the supervision of Professor Jose Antonio Lozano. (Machine Learning group and Scientific Director of BCAM)

Topics: Artificial Intelligence, Machine Learning and Temporal Data.

Skills/Qualifications

Good communication and interpersonal skills.
Ability to effectively communicate and present research ideas to researchers with different background.
Ability to clearly present and publish research outcomes in spoken (talks) and written (papers) form.
Good command of spoken and written English.
Good programming skill in R or python languages
Specific Requirements

The preferred candidate will have:

Research experience and interest in Artificial Intelligence in general with particular emphasis in areas such as: machine learning and mining of temporal data
Experience on analysis of very large datasets, preferably containing temporal data
Experience in working with real AI problems
Experience on the mathematical modelling of problems and algorithms in AI


More information: http://www.bcamath.org/en/research/job/postdoctoral-fellowship-in-artificial-intelligence-ai2019

Contract and offer: 14 months (starting in November 2019)
Deadline: October 18th 2019, 14:00 CET (UTC+1)
Salary: The gross annual salary of the Fellowship will be 28.000 – 32.000€. There is a moving allowance for those researchers that come from a research institution outside the Basque Country from EUR 1000 to EUR 2000 gross.
How to apply: Applications must be submitted online at www.bcamath.org/en/research/job

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The Engineering Management and Decision Sciences division at the College of Science and Engineering, Hamad Bin Khalifa University (HBKU) - Qatar seeks applications for a Post-Doctoral Position in the area of Logistics and Supply Chain and Operations Management to start as soon as possible. The position is typically for one year with possibility of additional yearly extensions depending on the research performance of the Post-Doctoral researcher. The position is full-time at HBKU in Qatar and a competitive financial package of about $88,000 (tax free) per year is provided. Review of applicants will begin immediately. The posting is expected to remain open until the position is filled.


Required Qualifications & Skills for the Post Doc positions
· Applicants should hold a Ph.D. in Industrial Engineering, Operations Research, Supply Chain Management or related field from a reputable university
· Applicants should have strong modeling and mathematical skills as well as coding and mastering appropriate optimization and simulation packages

· Applicants must be active researchers with demonstrated good record of scholarly journal publications in one of the above-mentioned research streams or related topics

· English language proficiency is a must.


Application Procedure:
To apply, please e-mail your curriculum vita, to Dr. chefi Triki at ctriki@hbku.edu.qa



About HBKU:

Hamad Bin Khalifa University (HBKU), a member of Qatar Foundation for Education, Science, and Community Development (QF), was founded in 2010 to continue fulfilling QF’s vision of unlocking human potential. HBKU is a homegrown research and graduate studies University that acts as a catalyst for positive transformation in Qatar and the region while having a global impact.

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You will be a member of the discrete mathematics group. Many important activities in mathematics are organized on a national level in the Netherlands. We are actively involved in these national efforts, for instance through the national research cluster DIAMANT and the NETWORKS programme. We also contribute to the national programme Mastermath by offering courses on a master/PhD level.

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The Department of Economics and Finance at LUISS has some openings for postdocs two of them on the following research projects:

- Stochastic methods in algorithmic game theory, Prof. Marco Scarsini.

A notice of competition by way of comparative evaluation is hereby issued for the awarding of 1 research grant at the Department of Economics and Finance of Luiss Guido Carli in the scientific area of Mathematics.

- Games on networks and Markov chains, Prof. Marco Scarsini.

A notice of competition by way of comparative evaluation is hereby issued for the awarding of 1 research grant at the Department of Economics and Finance of Luiss Guido Carli in the scientific area of Mathematics.

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Borsa della durata di 8 mesi (scadenza 2 ottobre 2019, ore 13.30) sulla gestione ottimizzata del controllo glicemico nel paziente perioperatorio. La sede
di lavoro e' Firenze (Careggi e Dipartimento di Ingegneria dell'Informazione).

Per ulteriori informazioni potete contattare:
Paola Cappanera (paola.cappanera@unifi.it) o Maddalena Nonato (maddalena.nonato@unife.it)

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We are looking for a highly motivated and creative post-doctoral researcher
to work on the ERC funded project Symmetry in Computational Complexity
(CoCoSym) under the supervision of Libor Barto at the Department of
Algebra, Faculty of Mathematics and Physics, Charles University, Prague.

The project concerns the complexity and approximability of fixed-template
constraint satisfaction problems over finite domains and their
generalization to infinite domains and weighted relations.

The duration of the position will be between one and three years. The
starting day is flexible, applications will be considered until the
position is filled. The position carries no teaching load. The position is
fully funded from the ERC grant, funding for conference travel is also
available.

Applicants should send a CV, a statement of research experience and
interests, and a list of publications (that may include a short annotation
of at most three of their best papers) in a single PDF file to Libor Barto (
libor.barto@mff.cuni.cz). Applicants should also arrange for at least two
recommendation letters to be sent directly to the same email address.
Informal inquiries are welcome.

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One postdoc position within the ERC Advanced Grant project "Algorithmic and
Mechanism Design Research in Online Markets" (AMDROMA) led by Stefano
Leonardi is available at Sapienza University of Rome.

The project AMDROMA considers research questions in algorithms and
mechanism design that are central for large-scale online markets. The focus
of the work will be on the development of new algorithmic data analysis
methods for online and streaming computation in clustering and matching.
The project also intends to apply these new methods to provide algorithmic
solutions for online market applications under various constraints such as
fairness, privacy, truthfulness, etc. The research will focus on
theoretical investigation, data driven modeling, and experimental
validation.

The research work will be carried on under the supervision of Prof. Stefano
Leonardi and Dr. Chris Schwiegelshohn.


Postdocs of AMDROMA are expected to contribute in defining research
problems of interest of the project, finding and analyzing novel solutions,
writing research papers, and collaborating with PhD students and other
postdoctoral researchers. Applicants should hold a PhD or be close to
complete a PhD in computer science, computer engineering, or related
fields.

There are two levels for the position: Junior and Senior Postdoctoral
Researcher. Fresh PhDs will be considered for the first level and everybody
else for both levels.


The position can start as soon as possible. The position can be extended up
to three years. Salary is competitive at the European level.


Applications including a CV and a statement of research should be sent to

Stefano Leonardi leonardi@diag.uniroma1.it

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Integrated models for the dimensioning and location of charging electric vehicles stations in the presence of renewable energy sources: Models and Algorithms

Luce Brotcorne
INRIA
Contact: Luce.Brotcorne@inria.fr

OVERVIEW
We are seeking candidates for a 1-year post-doctoral fellowship position starting autumn 2019 to work in the INOCS team at INRIA Lille Nord-Europe (https://team.inria.fr/inocs/).
This fellowship is part of a PGMO project (Gaspard Monge Program for Optimization, Operations Research and their interactions with Data Science).
The project is a joint project between INRIA Lille (Luce Brotcorne), University of Edinburgh (Miguel Anjos) and EDF (Riadh Zorgati).

GOALS
The purpose of this project is to locate and determine the number of charging stations to be installed in motorway service areas, taking into account the behaviour of road users and the expected quality of service. We consider that charging stations can include a local renewable energy production source as well as a battery to store energy.
The goal of the project is to develop integrated models for the problem as well as matheuristics algorithms to address large instances and instances based real life data.

SPECIFICATIONS
The candidate must have a PhD in Computer Science, Operations Research, Applied Mathematics. The candidate should demonstrate a solid background in mathematical programming.
Computer science skills in algorithmic and C/C++ development are also required. Knowledgement in stochastic programming is highly desirable.


How to Apply: The candidate must send by email until September 30, 2019 the following documents:

* Curriculum vitae with a list of publications, and previous experience.
* A recommendation letter from a previous supervisor (sent directly to Luce Brotcorne)
* A cover letter for the application.

All documents must be sent to Luce Brotcorne at Luce.Brotcorne@inria.fr

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The Max Planck Institute for Informatics is looking for excellent
female computer scientists, offering them PostDoc positions to develop
their scientific ideas without exertion of influence. The PostDoc
positions are funded by the Lise Meitner Award. It is a two-year
tax-free postdoctoral research fellowship including business expenses.
This grant is according to the fellowship rules of the Max Planck
Society: it usually amounts to 3,000 Euro/month and is completed by
compensation for business expenses of 10,000 Euro/year.

Fellows will be chosen based on the strength of their academic
background and research credentials. Applications should include a CV,
a cover letter, a publication list, a short research plan (one page is
enough), and two references, that will be contacted later to provide
recommendation letters.

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Optit (www.optit.net) is looking for young talents in OR to reinforce its OR team.
You will join a fast growing group of skilled OR specialist, working closely with data scientists (BI, ML, ..), a full stack internal SW development factory and business consultants, to qualify, design, develop and deliver top notch DSS in Energy & Utilities, Logistics and Transportation, Services and other industries, in Italy and abroad.
We expect good modelling and implementation skills, passion for innovation and application of OR in the real world, teamworking and entrepreneurship. We offer a stimulating and dynamic working environment, growth opportunities, international vision.
Our offices are based in Bologna and Cesena, but we may consider adoption of flexible smart working approach.

E-mail: jobs@optit.net

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Multiple Postdoc positions available at Université libre de Bruxelles
(ULB), Brussels, Belgium

Flexible start date. Research will be conducted within the Algorithms Group
(http://algo.ulb.be/).

The positions would be to work on a project entitled “Efficient data
structures and algorithms for modern computing devices in the age of big
data.” with Prof. John Iacono (http://di.ulb.ac.be/algo/iacono/).
Candidates are expected to have expertise and a history of publications in
one or more of the following: algorithms, data structures, algorithm
engineering, algorithms for modern hardware.

Applications (cover letter and CV) should be sent to postdoc@JohnIacono.com.

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Development of an integrated decision support system (DSS) for the management of irrigation distribution systems.
The aim is to obtain an increase in crop yield, minimize water waste and optimize the functioning of the hydraulic network by means of appropriate optimal irrigation scheduling.

Reference e-mail: cristiana.bragalli@unibo.it

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Centrum Wiskunde & Informatica (CWI) (Amsterdam) has vacancies in the Networks and Optimization research group for two talented PhD students / Early Stage Researchers on the subject of Polynomial Optimization, Efficiency through Moments and Algebra within the research consortium POEMA.

POEMA is a Marie Skłodowska-Curie Innovative Training Network (2019-2022), which offers 15 PhD positions within the full consortium, including two at CWI. Its goal is to train scientists at the interplay of algebra, geometry and computer science for polynomial optimization problems and to foster scientific and technological advances, stimulating interdisciplinary and intersectoriality knowledge exchange between algebraists, geometers, computer scientists and industrial actors facing real-life optimization problems.

The proposed PhD projects are investigating the development of new algebraic and geometric methods combined with computer algebra techniques for global non-linear optimization problems and their applications. The PhD positions at CWI will focus on polynomial optimization problems with applications to combinatorial optimization and quantum information theory.

The positions are expected to start from October 2019 (at the latest per 1 January 2020).

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Microlise is one of Europe's largest telematics and transport management
solutions providers with the HQ in Nottingham, Our mission is to empower
our customers such as Tesco, Sainsbury's, DHL, ASDA, Waitrose, Co-op, Eddie
Stobart, Royal mail, MAN, DAF, TATA to reduce their costs and environmental
impact by maximising the efficiency of their transportation operations. We
achieve this with our great employees who continue to develop and deploy
innovative, industry-leading technology solutions and services that enable
our customers to optimise fleet utilisation and driver performance, to
reduce costs and to improve service delivery.

The Data Science and Research team which consists of four PhD-level Data
Scientists, a Junior Data Scientist and a senior Research Programmer
collaborate with a number of universities on various R&D projects and
MSc/PhD research studies as well as work on a great variety of
collaborative R&D projects with partners and customers globally in the area
of Operational Research, Predictive modelling, Analytics, and Artificial
Intelligence.

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Applications for fully funded Ph.D. and post-doc 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 the collective capabilities to model and solve
hard optimization problems and the understanding of how external data
sources and real-time data can be used to improve the decision-making
process.

* 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
- OR based algorithms to efficiently solve machine learning problems

Research applications may include domains such as Logistics and
Transportation (e.g., vehicle sharing systems, facility location, network
design), Telecommunications, and Revenue Management (e.g., assortment
planning; discrete choice models).

>>> Particularly applications are invited for a post-doc position on machine
learning and optimization for high-frequency limit-order book data.
This position is at the Department of Finance at HEC Montréal
and interested candidates are encouraged to apply as soon as possible. <<<

* 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 renowned 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 offers a 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 for a PhD position should have a
Masters degree (or equivalent) in Computer Science, Operations Research,
Applied Mathematics, or a related field. Candidates for post-doc positions
should have a PhD in the aforementioned domains. All candidates should
belong to the top of their academic classes and demonstrate good
programming and mathematical 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)
- results of GRE or GMAT (if available)

If you have further questions regarding these positions, possible research
topics, etc., please contact Sanjay Dominik Jena (sanjay.jena@cirrelt.ca).
For a start in January 2020, admission deadline is end of August 2019 at
most of the universities. We therefore encourage to apply early, since, if
considered for the entry at a Business school, a GRE/GMAT will be required
which takes some time of preparation. Post-doc positions do not have
specific starting dates.

Toggle description

Delivery of products purchased by online customers is an increasingly important problem for e-commerce companies, representing a substantial para of their costs. The final step --- last mile delivery, which conveys the product to the customer --- is a key stage in the process.
Several business models proposed recently exploit the concept of crowdsourcing in which, in addition to professional couriers, ordinary citizens are invited to participate in the delivery process. However, current models present a set of weaknesses and do not adequately address many of the concerns associated with real-world implementation.

This project will address such concerns. The main concept is to have in-store customers delivering parcels on their way home to customers that ordered on-line, besides maintaining a backup of professionals for delivering the remaining parcels. This approach will reduce environmental impacts and urban congestion at low marginal cost to the company.

Optimization
The underlying problem associated to LastMile can be modeled as a mixed-integer optimization problem. The most elementary models are deterministic, but for realistic outcomes they must be extended to stochastic contexts. We expect that the solution process will involve a intricate framework, making use of optimization solvers as well as ad hoc components specific to this problem.

Machine learning
An important part of the problem involves modeling the probability of acceptance for outsourcing tasks, as well as their impacts on delivery costs. This will involve dynamically analyzing data and extracting relevant information, making use of the state-of-the-art in machine learning.

Steps
•Modeling practically relevant situations yet unaddressed
•Researching new compensation schemes for guaranteeing sustainability of the models
•Researching efficient optimization algorithms for simultaneously matching parcels to couriers and optimizing the routes of the firm’s own fleet.

Keywords:
•Vehicle routing
•Transportation
•Stochastic programming
•Machine learning

Key competences:
•Mathematical modeling and optimization
•Stochastic modeling
•Computer programming


Project team
João Pedro Pedroso - http://orcid.org/0000-0003-1298-7191
Ana Viana - http://orcid.org/0000-0001-5932-5203
Xenia Klimentova - http://orcid.org/0000-0003-1085-0810
Pierre Hosteins - http://orcid.org/0000-0003-4186-9127
Katarzyna Gdowska - http://orcid.org/0000-0002-7964-3724
Abdur Rais - http://orcid.org/0000-0003-1906-9684

Toggle description

A PhD student position, funded through a full-time research and teaching
assistantship, is available at HEC Liège – Management School of the
University of Liège.



The successful candidate will prepare a doctoral thesis in the fields of
operational research and supply chain management under the supervision of
Prof. Yasemin Arda. The thesis subject will be related to the current and
future research projects of the group on operational research methods
(mathematical modelling and optimization, stochastic programming,
combinatorial optimization, exact solution approaches (e.g.,
branch-and-price), heuristic solution approaches (e.g., metaheuristics),
etc.) and their applications in supply chain management (network design,
production planning, scheduling and sequencing, vehicle routing, pricing,
healthcare operations management, etc.).

Toggle description

Behavioural change is an important factor in the maintenance of health and well-being in a number of conditions; a change in a person's behaviour can often be an indication of a change in their health state. Monitoring behaviour and detecting change as part of self-management can therefore be an effective tool for the maintenance of stable health in chronic diseases.
By monitoring behaviour, changes that correlate to prodromes or early warning signs can be identified and corrective or preventative action taken early. The activity will be devoted to the characterization of common patterns and in the identification of pattern change in time series of behavioral data. In particular, the development of data visualization techniques, clusting models and anomaly detection in behavioral data will be required.

Reference e-mail:
enza.messina@unimib.it

Toggle description

Hydrogen is the only carbon-free storable fuel. When combined with
renewable energy sources (wind, solar, hydro, wave and tidal), it has the
potential to become one of the main contributors of a sustainable future as
a green energy vector. The project aims to handle dynamic management of a
decentralized Power-to-Hydrogensystem where electricity is converted into
hydrogen fuel for a zero-emission mobility. Multiple economic agents with
conflicting interests are involved in the renewable electricity-based
hydrogen supply chain.

This PhD thesis will focus on bilevel modeling the Stackelberg game played
between two decision makers: a renewable energy supplier and a hydrogen
asset operator. The former competes in a day-ahead energy spot market and
offers other services (such as ancillary services) besides energy while
facing an uncertain energy generation, changing spot prices and a varying
demand. The latter focuses on producing hydrogen while respecting
operational constraints and limitations at a minimum cost.

Bilevel programs are inherently hard to solve, especially under
uncertainty. Therefore, there will be a strong emphasis on finding
efficient exact and/or heuristic solution methodologies. Different types of
real-life or realistic data will be available for testing.

We are offering a 3-year CIFR PhD thesis at PersEE Innovation, a Lyon-based
startup company (Sezin Afsar), in collaboration with Ecole des Ponts
ParisTech (Michel De Lara).

Keywords: supply chain, renewable energy, hydrogen, stochastic
optimization, bilevel optimization, game theory

Required Technical Skills:
• Master’s degree or equivalent in Industrial Eng, Computer Science,
Applied Math or any relevant subject from a European institution
• Experience in Python/C/C++ and solvers such as GAMS, CPLEX or Gurobi
• General knowledge of mathematical programming and optimization. Expertise
in stochastic and integer programming is an advantage.
• Familiarity with at least one of relevant fields (energy systems and
markets,
renewable energy, supply chain management, metaheuristics…)

Behavioral Skills:
• Adaptability to team work
• Curiosity and enthusiasm to learn
• Flexibility
• Being open to new ideas and innovations
• Willingness to contribute to a cleaner future
• Speaking French is a plus

Candidates may send their CV, transcript, motivation letter and references
to saf@pers-ee.fr until 16/08. Start date will be 01/12