PHD Postion in Area of Causal Inference

AcademicTransfer; Netherlands; On-site; EUR 36,000 - 45,000; Full time

Benefits offered by this job

8% holiday allowance

8.3% end-of-year bonus

commuting expense contribution

personalized benefits package

up to 41 days annual leave

work-life balance schemes

Job summary

Vrije Universiteit Amsterdam invites applications for a fully-funded 4-year PhD position in causal inference within the Safe Causal Inference consortium. You will join a team of researchers across the Netherlands to study evaluation methods for conditional causal effects.

The role combines research and teaching duties, with English communication and a start date ideally before 01.02.2027. The remuneration follows Dutch university scales, with generous benefits and a strong emphasis on inclusion

Qualifications

• MSc in Mathematics, Statistics or Econometrics (or equivalent).
• Strong background in statistics and causal inference.
• Good communication skills in English.

Responsibilities

• conduct research toward writing a PhD thesis
• teaching tasks (approx. 15% of time)
• collaborate in the Safe Causal Inference project and supervise related activities

Skills

Experience with causal inference

Good communication skills

Programming in R or Python

Education

MSc in Mathematics/Statistics/Econometrics

Tools

R

Python

Job description

Organisation/Company Vrije Universiteit Amsterdam (VU) Research Field Mathematics » Statistics Researcher Profile First Stage Researcher (R1) Application Deadline 25 Sep 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

The Department of Mathematics of Vrije Universiteit Amsterdam welcomes applications for a fully-funded, 4-year PhD position in causal inference.
You will join the “Safe Causal Inference” consortium. Causal inference studies what assumptions are needed, and which methods you can use when those assumptions are met, to reliably conclude that “A causes B” and not just “A is correlated with B”. The consortium aims to incorporate all uncertainties into causal inferences, combining information obtained under alternative assumptions. In a team of 8 PhD researchers and 5 Principal Investigators located throughout the Netherlands, you’ll join us in developing a novel, iterative approach to causal inference that combines the strengths of subject-matter knowledge and the flexibility of data-driven algorithms.
You will work on the subproject “Triangulation of performance assessment methods for conditional causal quantities”. This PhD project investigates how to reliably assess the performance of estimators of conditional causal effects (such as CATE estimators and predictions under interventions). The core problem is that evaluating an estimator requires counterfactual outcomes in the evaluation dataset, but deriving those outcomes itself relies on causal assumptions, meaning the evaluation can be just as assumption-dependent as the estimator it's meant to assess.
You will examine whether combining evaluation results across different datasets, different causal assumptions, and different evaluation approaches (counterfactual, factual, and benchmarking against trials) leads to a more complete and reliable picture of a causal relationship. The goal is to develop a framework that helps data analysts choose the best evaluation strategy depending on which assumptions they are willing to make.
You will be jointly supervised by dr. Stéphanie van der Pas (VU), dr. Nan van Geloven (LUMC) and dr. Jeremy Labrecque (ErasmusMC). Your main working location will be the Mathematics department at Vrije Universiteit Amsterdam, where you will join dr. Stéphanie van der Pas’ research group on causal inference.
We are an inclusive, interdisciplinary group, and diversity and internationalism is at the heart of our research principles, as well as our teaching practice.
The preferred starting date is: as soon as possible, ideally before 01.02.2027.
Applications from all groups currently under-represented in academic posts are especially encouraged. We particularly welcome applications from women and people with an ethnic minority background.

Your duties

• doing research towards writing a PhD thesis
• teaching tasks (roughly 15% of your time), for instance supervising exercise classes
• a (prospective) MSc. degree in Mathematics, Statistics or Econometrics (or an equivalent thereof)
• good communication skills in English

Priority will be given to candidates with:

• a strong background in statistics
• experience with causal inference
• affinity with programming in R or python

Additional Information

A challenging position in a socially involved organization. On full-time basis the remuneration amounts to a minimum gross monthly salary of €3204 (at the start) and a maximum €4051 (in the fourth year). The job profile is based on the university job ranking system and is vacant for 1.0 FTE.
The appointment will initially be for 1 year. After a satisfactory evaluation of the initial appointment, the contract will be extended for a further 3 years. Additionally, Vrije Universiteit Amsterdam offers excellent fringe benefits and various schemes and regulations to promote a good work/life balance, such as:

• 8% holiday allowance and 8.3% end-of-year bonus
• contribution to commuting expenses
• optional model for designing a personalized benefits package
• a maximum of 41 days of annual leave based on full-time employment
• good paid parental leave scheme