PhD in Causal Inference & Machine Learning: The Delft University of Technology (TU Delft) is offering a PhD position focused on Causal Inference and Machine Learning. This position is part of the “Safe Causal Inference” consortium, aiming to improve the trustworthiness of causal claims in various fields. Candidates will engage in cutting-edge research to develop methods for detecting and mitigating causal assumption violations.
PhD Scholarship Opportunity in Causal Inference & Machine Learning
Designation
PhD Candidate in Causal Inference & Machine Learning
| Detail | Information |
|---|---|
| Research Area | Causal Inference, Machine Learning |
| Location | TU Delft, Netherlands |
| Salary Range | € 2901 – € 3707 per month |
| Hours per Week | 38-40 hours |
| FTE | 1.0 |
| Duration of Employment | 4 years with an initial 1.5-year contract |
Eligibility/Qualification
- Master’s degree in a relevant quantitative field (statistics, computer science, mathematics, econometrics, epidemiology, psychometrics, or physics).
- Strong interest in statistical and machine learning methods.
- Proficient programming skills in Python, R, Julia, or similar languages.
- Excellent spoken and written English skills.
Description
This PhD project aims to advance causal inference methodologies by identifying causal assumption violations, developing new detection methods, and integrating these insights into causal models. The candidate will collaborate with a multidisciplinary team of experts and will be supervised by leading academics in the fields of computer science and epidemiology. TU Delft provides a stimulating research environment, and successful candidates will have opportunities for professional development.
How to Apply
Interested candidates should submit their applications via the online application button, including the following documents:
- CV
- Cover letter (maximum 2 pages) detailing motivation, research interests, and relevance to the position.
Contact for Queries: Dr. Jesse Krijthe, Email: j.h.krijthe@tudelft.nl
Last Date to Apply
Applications are accepted until July 9, 2025.
