PhD-TA Reliability of Dynamic Flow Networks

PhD-TA Reliability of Dynamic Flow Networks

Published Deadline Location
13 Mar 21 Apr Eindhoven

Job description

Would you like to contribute to preventing large-scale failures or congestion in stochastic flow networks? Are you excited about an opportunity to teach and supervise students in the area of Applied Probability and Stochastic Operations Research? We offer a PhD-TA position (75% research, 25% teaching) on the topic of 'Emergence of heavy tails in stochastic flow networks'. In this research project, you will explore why major failures or congestion phenomena emerge in efficiently-operated flow networks (e.g. road networks or power grids), as well as the role of the underlying network topology. Armed with these insights, you will design efficient strategies to drastically reduce the probability of large-scale failures/congestion as well as the magnitudes of these adverse events.

Job Description

Understanding the emergence of major failures or congestion effects in flow networks is of critical importance as these occur in various application domains: blackouts in power grids, traffic jams in road or rail networks, congestion in computer networks and more. It is particularly alarming when the sizes of such disruptions are heavy-tailed, as this implies that the probability of large-scale failures or congestion is substantially higher than conventional statistical laws might suggest, and that therefore such catastrophes cannot be dismissed as virtually impossible events. Surprisingly, a fundamental understanding of the emergence of heavy tails (using a rigorous mathematical approach) is still lacking to this day, as are sound preventive measures.

In this project, you will analyze networks where traffic flows through the network in a (cost-)efficient manner, but is subject to congestion or even failure whenever the traffic load exceeds capacities. You will explore the effect of network topology, and use these insights to design strong mitigation strategies: for example, by determining where upgrading network capacities or introducing additional routes is most beneficial. Moreover, you will develop intervention methods for flow redistribution to prevent overall failures/congestion from cascading or causing a total network collapse.

As a PhD-TA, you will also be crucially involved in educational activities in the area of stochastic processes and applied probability. Depending on your interests, you can contribute as an instructor, lecturer or (co-)supervisor of BSc and MSc final projects. You will have the unique opportunity to spark students' interest in this area, and help students develop the skills and obtain the knowledge needed to excel in their future career.

This position is in the Statistics, Probability and Operations Research (SPOR) cluster in the Mathematics and Computer Science (M&CS) Department at Eindhoven University of Technology (TU/e). The SPOR cluster has a vibrant research environment, accommodating strong scientists with diverse backgrounds from Applied Probability to Discrete Optimization. In particular, you will be a member of the Stochastic Operations Research group, which focuses on evaluating and optimizing the performance and reliability of large-scale systems that operate in the presence of randomness and uncertainty. We develop mathematical models and methods for the design, analysis, optimization and control of such systems with techniques at the intersection of Applied Probability and Operations Research. At the heart of the SPOR cluster is the workshop institute EURANDOM, offering major opportunities for you to learn through various international workshops and even co-organize workshops.

Specifications

Eindhoven University of Technology (TU/e)

Requirements

We are a looking for a strong PhD candidate who is excited to work in the area of dynamic flow networks. Key characteristics of an ideal candidate include:
  • A MSc degree in mathematics, with specialization in (Applied) Probability Theory, Stochastic Operations Research, and Optimization.
  • Familiarity with large deviations theory, asymptotic analysis, (convex) optimization techniques, random graph theory and (general) resource allocation algorithms/scheduling.
  • Strong independency in analytical thinking, and intrinsic drive to deep thinking and complex problem solving.
  • Enthusiasm to contribute to the educational activities in the area of Applied Probability.
  • Great communication skills, excellent team-working capabilities, strong academic writing competences, and fluency in English (CEFR level C1 or above).

Conditions of employment

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:
  • Full-time employment for five years, with an intermediate evaluation (go/no-go) after nine months. You will spend 25% of your employment on educational tasks. Typically, your final year will be used solely for research.
  • Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. €2,770 max. €3,539).
  • A year-end bonus of 8.3% and annual vacation pay of 8%.
  • High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
  • An excellent technical infrastructure, on-campus children's day care and sports facilities.
  • An allowance for commuting, working from home and internet costs.
  • Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

Additional information

About us



Eindhoven University of Technology is an internationally top-ranking university in The Netherlands which combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow. 

Curious to hear more about what it's like to be a PhD candidate at TU/e? Please watch the video.

Information

Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager dr. Fiona Sloothaak, f.sloothaak@tue.nl, or prof. Sem Borst, s.c.borst@tue.nl

Visit our website for more information about the application process or the conditions of employment. You can also contact our personnel officers Jonelleke Kamperman or Gaby Jansen, HRServices.MCS@tue.nl.

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application

If you are interested, we invite you to apply as soon as possible by using the 'apply now' button. We will start considering applications and interviewing immediately upon receiving an application. The application should include a:
  • Cover letter (1 page max), which includes a motivation of your interest in the vacancy and an explanation of why you would fit well for the project;
  • An extensive curriculum vitae (including a list of possible publications and awards);
  • Your MSc thesis and BSc thesis (if applicable);
  • A course list of your BSc and MSc programs (including grades);
  • Names and contact information of two references;
  • Any further information that might be relevant.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.

Specifications

  • PhD
  • Engineering
  • max. 38 hours per week
  • University graduate
  • V32.7331

Employer

Eindhoven University of Technology (TU/e)

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Location

De Rondom 70, 5612 AP, Eindhoven

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Application procedure

Application procedure

Make sure to apply no later than 21 Apr 2024 23:59 (Europe/Amsterdam).