PhD in Computational Probability at Delft University of Technology

Delft University of Technology has an opening PhD position in mathematical physics. Applicants should apply as soon as possible.

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) is known worldwide for its high academic quality and the social relevance of its research programmes. The faculty's excellent facilities accentuate its international position in teaching and research. Within this interdisciplinary and international setting the faculty employs more than 1100 employees, including about 400 graduate students and about 2100 students. Together they work on a broad range of technical innovations in the fields of sustainable energy, telecommunications, microelectronics, embedded systems, computer and software engineering, interactive multimedia and applied mathematics.

Research at the Delft Institute of Applied Mathematics (DIAM) centres around the analysis of mathematical models arising in science and engineering. This research is both fundamental and applied in nature, and is often inspired by technical applications. The department plays an active role in translating research results into concrete, practical applications. It maintains intensive contacts with other TU Delft departments, the major technological institutes, and the research laboratories of major companies. Within its own subject field, the department provides teaching for the Applied Mathematics BSc and MSc programmes, and also contributes to the teaching of mathematics courses within other academic programmes at the TU Delft and within national programmes such as "MasterMath".

The Delft Institute of Applied Mathematics consists of six research groups: Analysis, Mathematical Physics, Numerical Analysis, Applied Probability, Statistics, and Optimisation. More information about the Delft Institute of Applied Mathematics can be found at

Markov Chain Monte Carlo (MCMC) is a probabilistic computational method which is of vital importance in data science (statistics, machine learning) as well as in the physical sciences (physics, chemistry, biology). For example, MCMC is applied for training of (deep) neural networks, as well as for the simulation of many-particle systems.

In recent years the MCMC community has developed fundamentally new algorithms in this family, based on Piecewise Deterministic Markov Processes (PDMPs). Important examples are the Zig-Zag Sampler (Bierkens et al., 2017) and the Bouncy Particle Sampler (Bouchard-Ct et al, 2017). Already these methods are showing excellent (sometimes even groundbreaking) computational efficiency. To highlight the importance of this new approach, the Dutch science foundation (NWO) has awarded the research project on this topic – funding this Phd project – with a prestigious Vidi grant.

In order to apply these new methods in practice it is crucial to first obtain a solid theoretical understanding of these stochastic algorithms. This means delving into the mathematical properties of PDMPs and will therefore be a fascinating challenge for aspiring mathematicians with a strong interest and solid background in probability theory. The answers to the research questions in this project will contribute to guidelines on designing an optimal PDMP sampler for a given computational task. Given the theoretical nature of this project a background in stochastic processes and/or stochastic calculus is highly desirable.

- Strong curriculum in the mathematical theory of stochastic processes

TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children's Centre offers childcare and an international primary school. Dual Career Services offers support to accompanying partners. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.

As a PhD candidate you will be enrolled in the TU Delft Graduate School. TU Delft Graduate School provides an inspiring research environment; an excellent team of supervisors, academic staff and a mentor; and a Doctoral Education Programme aimed at developing your transferable, discipline-related and research skills. Please visit for more information.

For information about this vacancy, you can contact J. Bierkens, email:, tel: +31 15 27 84593.

Provisional starting date: 1 January 2019 (flexible). Interviews expected to be held in November 2018.

When applying please send your materials before November 1, 2018 to stating vacancy number EWI2018-58.

For information about the selection procedure, please contact Mrs. Paula van den Bergh, HR-Advisor, email:


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