PhD-TA Resilience of Dynamic Flow Networks

Are you eager to use your mathematical skills to improve the reliability and resilience of dynamic flow networks? Do you want to develop probabilistic techniques to prevent major failures and congestion in critical infrastructures, like road networks and power grids? We invite applications for a PhD-TA position (75% research, 25% teaching) in Applied Probability and Stochastic Operations Research. You will explore why major failures or congestion phenomena emerge in efficiently-operated flow networks, as well as the role of the underlying network topology. Armed with these insights, you will develop efficient strategies to drastically reduce the probability and impact of massive disruptions.

Understanding the emergence of massive 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 these disruption sizes are heavy-tailed, as this implies that large-scale calamities, while rare, are not virtually impossible. 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. 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.

We are 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.
• Preferably some 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 stochastic processes.
• Great communication skills, excellent team-working capabilities, strong academic writing competences, and fluency in English (CEFR level C1 or above).

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 teaching tasks.
• 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. €2,901 max. €3,707).
• 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.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

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.

We invite you to submit a complete application by using the apply button. 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.