AIRO Young Opportunity
PhD position in Algorithmics
(Academia)
Expires
01 Jan 2021
Institution
Faculty of Electrical Engineering, Mathematics & Computer Science, TU Delft
Country
The Netherlands
Description
PhD position on the intersection of combinatorial optimisation and machine learning to deliver novel trustworthy, safe, and explainable machine learning algorithms.
Job description
Challenge: Safe, explainable, and trustable machine learning
Change: Replace machine learning heuristics with rigorous and verifiable optimisation methods
Impact: Machine learning algorithms that can trusted with important decision-making in society
We are seeking a highly motivated candidate to work on the intersection of combinatorial optimisation and machine learning to deliver novel trustworthy, safe, and explainable learning algorithms. Machine learning has seen tremendous progress in the past decades. When deploying in practice, however, guaranteeing that machine learning algorithms can be trusted to maximise the desired utility is still a challenging problem. For example, we must ensure the algorithms do not implicitly discriminate based on race or gender, but this unfortunately is not readily available with conventional methods. The PhD student will contribute towards trustworthy machine learning by developing innovative techniques based on ideas typically associated with the field of combinatorial optimisation or other approaches proposed by the candidate. The resulting algorithms are foreseen to be applied to a variety of application domains, e.g., bioinformatics, automated controller design, and data-driven policy making.
Responsibilities:
Perform scientific research in the area of combinatorial optimisation and machine learning
Implement and evaluate research prototypes
Write and publish scientific reports at international venues, e.g., conferences and journals
Present results at international conferences
Collaborate with domain experts
Participate in activities of the research group
The PhD student will be supervised by Dr Emir Demirović and Dr Mathijs de Weerdt from the Algorithmics research group at TU Delft.
Requirements
Key requirements:
MSc degree in Computer Science, Artificial Intelligence, Mathematics, or a closely related field
Excellent algorithmic and programming skills
Excellent command of English, both written and spoken
Excellent interpersonal skills and teamwork spirit
Desirable skills:
Knowledge of statistics or machine learning
Knowledge of combinatorial optimisation, e.g., operations research, constraint programming, Satisfiability solving, discrete mathematics
Programming in C/C++
Conditions of employment
TU Delft offers PhD-candidates a 4-year contract, with an official go/no go progress assessment after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2395 per month in the first year to € 3061 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.
The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.
The PhD student will an employee of TU Delft and will accordingly receive social security, e.g., health insurance, contribute to pensions funds, paid leave, etc.
Non-EU citizens are welcome to apply and TU Delft will arrange necessary work permits.
TU Delft is committed to diversity and inclusion in its work place and invites individuals to apply regardless of their age, race, ethnicity, culture, gender, nationality, sexual orientation, physical ability, and background.
TU Delft (Delft University of Technology)
Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity and aim to be as inclusive as possible (see our Code of Conduct). Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.
Challenge. Change. Impact!
Faculty Electrical Engineering, Mathematics and Computer Science
The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three disciplines - electrical engineering, mathematics and computer science. Combined, they reinforce each other and are the driving force behind the technology we use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make future-proof. We are also working on a world in which humans and computers reinforce each other. We are mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. There is plenty of room here for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1,100 employees and 4,000 students work and study in this innovative environment.
Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.
Additional information
For more information about this vacancy and the selection procedure, please contact Dr Emir Demirović, Assistant Professor, email: e.demirovic@tudelft.nl.
Application procedure
Interested candidates are invited to send the following documents:
CV
Transcript of grades along with a description of the scores
Master thesis (or draft if not yet submited)
Summary of other scientific works (if applicable)
Motivation letter (explaining your interest in the position, why are you a good candidate for the job, and possibly your career goals)
A pre-employment screening can be part of the application procedure.
Job description
Challenge: Safe, explainable, and trustable machine learning
Change: Replace machine learning heuristics with rigorous and verifiable optimisation methods
Impact: Machine learning algorithms that can trusted with important decision-making in society
We are seeking a highly motivated candidate to work on the intersection of combinatorial optimisation and machine learning to deliver novel trustworthy, safe, and explainable learning algorithms. Machine learning has seen tremendous progress in the past decades. When deploying in practice, however, guaranteeing that machine learning algorithms can be trusted to maximise the desired utility is still a challenging problem. For example, we must ensure the algorithms do not implicitly discriminate based on race or gender, but this unfortunately is not readily available with conventional methods. The PhD student will contribute towards trustworthy machine learning by developing innovative techniques based on ideas typically associated with the field of combinatorial optimisation or other approaches proposed by the candidate. The resulting algorithms are foreseen to be applied to a variety of application domains, e.g., bioinformatics, automated controller design, and data-driven policy making.
Responsibilities:
Perform scientific research in the area of combinatorial optimisation and machine learning
Implement and evaluate research prototypes
Write and publish scientific reports at international venues, e.g., conferences and journals
Present results at international conferences
Collaborate with domain experts
Participate in activities of the research group
The PhD student will be supervised by Dr Emir Demirović and Dr Mathijs de Weerdt from the Algorithmics research group at TU Delft.
Requirements
Key requirements:
MSc degree in Computer Science, Artificial Intelligence, Mathematics, or a closely related field
Excellent algorithmic and programming skills
Excellent command of English, both written and spoken
Excellent interpersonal skills and teamwork spirit
Desirable skills:
Knowledge of statistics or machine learning
Knowledge of combinatorial optimisation, e.g., operations research, constraint programming, Satisfiability solving, discrete mathematics
Programming in C/C++
Conditions of employment
TU Delft offers PhD-candidates a 4-year contract, with an official go/no go progress assessment after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2395 per month in the first year to € 3061 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.
The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.
The PhD student will an employee of TU Delft and will accordingly receive social security, e.g., health insurance, contribute to pensions funds, paid leave, etc.
Non-EU citizens are welcome to apply and TU Delft will arrange necessary work permits.
TU Delft is committed to diversity and inclusion in its work place and invites individuals to apply regardless of their age, race, ethnicity, culture, gender, nationality, sexual orientation, physical ability, and background.
TU Delft (Delft University of Technology)
Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity and aim to be as inclusive as possible (see our Code of Conduct). Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.
Challenge. Change. Impact!
Faculty Electrical Engineering, Mathematics and Computer Science
The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three disciplines - electrical engineering, mathematics and computer science. Combined, they reinforce each other and are the driving force behind the technology we use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make future-proof. We are also working on a world in which humans and computers reinforce each other. We are mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. There is plenty of room here for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1,100 employees and 4,000 students work and study in this innovative environment.
Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.
Additional information
For more information about this vacancy and the selection procedure, please contact Dr Emir Demirović, Assistant Professor, email: e.demirovic@tudelft.nl.
Application procedure
Interested candidates are invited to send the following documents:
CV
Transcript of grades along with a description of the scores
Master thesis (or draft if not yet submited)
Summary of other scientific works (if applicable)
Motivation letter (explaining your interest in the position, why are you a good candidate for the job, and possibly your career goals)
A pre-employment screening can be part of the application procedure.