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Delft

PhD Position Mathematical Statistics

Delft Delft
3.059 tot 3.881
32 - 40 uur
nieuw
Status Open
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Wat wij vragen

Opleiding
MSc degree in Mathematical Statistics
Talen
  • Je beheerst Engels

Wat wij bieden

Salaris
€ 3.059 tot € 3.881
Uren
32 tot 40 uur per week
Dienstverband
fulltime
Type vacature
intern

Vacaturebeschrijving

The Department of Applied Mathematics in the Faculty of Electrical Engineering, Mathematics and Computer Science at the Delft University of Technology is seeking a hardworking PhD candidate

The goal of this position is to advance the state of the art and develop new theory and methodology for dependence models, in particular copula-based statistical models. Since the 1990s, copulas have become recognized as the main tool to model arbitrary dependence (not necessarily linear) between random variables, with applications in many quantitative fields, including finance and risk management, insurance, hydrology, and health.

This project consists of three main research directions. The first subproject is related with recent developments in the theory of conditional copulas and conditional dependence models. These are models that quantify the influence of a random vector X on the dependence between two random variables Y1 and Y2 of interest – or more. This has applications in particular in finance where some leading financial assets can influence the dependence between other assets. The goal is to recover the structure underlying a set of estimated conditional dependence functions, with a generalization towards conditional U-statistics.

The second subproject is to develop a theory of information geometry for copulas. Information geometry is a field at the interface between probability, statistics and geometry, and aims at getting geometrical information and structure on statistical problems, for example quantifying angles and directions in the space of probability measures – here in the space of copulas.

The third subproject is to integrate discrete random variables into the Pair-Copula Bayesian Networks (PCBNs) and develop structure learning algorithm. PCBNs models allow to decompose one difficult problem (the inference of a multivariate distribution/density) into smaller bivariate problems by using information on conditional independencies. Contrary to classical Gaussian Bayesian networks, the approach here relies on copulas with arbitrary margins.

These three projects are mostly independent and can be done in any order, also depending on the preferences of the successful candidate.

Job requirements
  • You hold or will soon complete a MSc degree in Mathematical Statistics or equivalent.
  • You have experience with programming in R. Experience with compiled languages such as C++ is a plus.
  • You have high-level mathematical skills and are curious to invent new models and theories.
  • You are fluent in English, both spoken and written.
Conditions of employment

Doctoral candidates will be offered a 4‑year period of employment in principle, but in the form of 2 employment contracts. An initial 1.5‑year contract with an official go/no‑go progress assessment within 15 months. Followed by an additional contract for the remaining 2.5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from €3059 to €3881 gross per month, from the first year to the fourth year based on a full-time contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.

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 customizable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

Relocation

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your social network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.

Additional information

If you would like more information about this vacancy or the selection procedure, please contact Dr. Alexis Derumigny, via a.f.f.derumigny@tudelft.nl.

Application procedure

Are you interested in this vacancy? Please apply no later than 14 June 2026 via the application button and upload the following documents:

  • CV
  • Motivational letter
  • Grades of BSc and MSc courses (if you have not finished your MSc studies, please upload a list of currently available grades that you have).

You can address your application to Dr. Alexis Derumigny.

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.

Please note:
  • You can apply online. We will not process applications sent by email and/or post.
  • As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
  • Please do not contact us for unsolicited services.

Faculty/Department: Faculty of Electrical Engineering, Mathematics & Computer Science

FTE: 1,0

Submission is possible until: 14 Jun 2026

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Salarisomschrijving

€3059 - €3881 monthly

Nu solliciteren

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Nu solliciteren

Solliciteer op de website van de werkgever


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