PhD Operations Research and Learning Techniques

PhD Operations Research and Learning Techniques

Published Deadline Location
13 Jul 12 Sep Eindhoven

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PhD position in the area of operations research and learning techniques. We aim to solve control and scheduling problems that arise in (large-scale) stochastic systems/networks by exploiting fundamental insights to develop smarter learning algorithms and improved dynamic control policies.

Job description

The project

For control or scheduling problems with large instances, there is typically an obstacle that relates to the curse of dimensionality. Asymptotic analysis or intuitive heuristics can sometimes help to reach a reasonable solution, but often enough, these types of problems are too complex to be solved with traditional (probabilistic) techniques alone. The world of data analytics offers various promising techniques to deal with this issue. In this project, the PhD candidate will combine traditional techniques from applied probability and optimization with data analytical tools to come to meaningful dynamic control policies for problems that arise in (large-scale) stochastic systems/networks.

The department

The project will be carried out at the Mathematics and Computer Science department of the Eindhoven University of Technology. The department has a vibrant international environment, with 46% of the scientific staff being non-Dutch nationals and more than 100 PhD candidates. The statistics and the stochastic operations groups are part of the SPOR (Statistics, Probability Theory and Operations Research) cluster within the TU/e subdepartment Mathematics. The SPOR-cluster currently has 4 full professors, 6 part-time professors, 3 associate professors and 14 assistant professors. In addition, the cluster is strongly intertwined with EURANDOM, the European institute for research in Statistics, Probability and Stochastic Operations Research. EURANDOM is a workshop and visitor centre that exists since 1998.

Specifications

Eindhoven University of Technology (TU/e)

Requirements

Applicants are required to have an MSc degree in mathematics or a related field, with a strong background in probability theory, operations research, and (stochastic) optimization. Proficiency in English is also required, and research experience will be highly valued. All applicants should include a cover letter, curriculum vitae, course list, and the contact information of two references.

Conditions of employment

  • A meaningful job in a dynamic and ambitious university with the possibility to present your work at international conferences.
  • A full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months.
  • To support you during your PhD and to prepare you for the rest of your career, you will make a Training and Supervision plan and you will have free access to a personal development program for PhD students (PROOF program).
  • A gross monthly salary and benefits (such as a pension scheme, pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labor Agreement for Dutch Universities.
  • Additionally, an annual holiday allowance of 8% of the yearly salary, plus a year-end allowance of 8.3% of the annual salary.
  • Should you come from abroad and comply with certain conditions, you can make use of the so-called '30% facility', which permits you not to pay tax on 30% of your salary.
  • A broad package of fringe benefits, including an excellent technical infrastructure, moving expenses, and savings schemes.
  • Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.
  • Information about terms of employment can be obtained from the HR officers, Ms.Jonelleke Kamperman and Ms. Gaby Jansen (HRServices.MCS@tue.nl).

Specifications

  • PhD
  • Engineering
  • max. 38 hours per week
  • University graduate
  • V32.5106

Employer

Eindhoven University of Technology (TU/e)

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Location

De Rondom 70, 5612 AP, Eindhoven

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