Summary
This scholarship offers a position for a PhD candidate to explore innovative methods in causal inference and machine learning, focusing on detecting and mitigating assumption violations. It is part of the “Safe Causal Inference” consortium, providing a collaborative environment across various disciplines.
Designation
PhD Candidate in Causal Inference & Machine Learning
Table
| Details | Information |
|---|---|
| Research Area | Causal Inference, Machine Learning |
| Location | TU Delft, Netherlands |
| Eligibility/Qualification | Master’s degree in relevant quantitative fields |
| Job Description | Research on causal methods and assumption violations |
| How to Apply | Apply online via the TU Delft website |
| Last Date for Apply | May 20, 2026 |
Research Area
The research focuses on innovative methodologies for causal inference, aiming to understand and tackle the limitations in detecting violations of causal assumptions, particularly in high-dimensional and longitudinal settings.
Location
The position is based in the Pattern Recognition and Bioinformatics group at TU Delft, in Delft, Netherlands.
Eligibility/Qualification
- Strong interest in statistical and machine learning methods.
- Master’s degree in a relevant quantitative field (e.g., statistics, computer science, mathematics, econometrics, psychometrics, physics).
- Proficiency in programming languages such as Python, R, or Julia.
- Proficient in spoken and written English.
Job Description
As a PhD candidate, you will engage in a groundbreaking project to better understand the limits in detecting causal assumption violations and develop new methods and procedures to ensure more trustworthy causal claims. You will work under supervision from experts in computer science and biostatistics.
How to Apply
Interested candidates should:
- Prepare a CV.
- Write a cover letter (max 2 pages) addressing your motivation, research interests, and their connection to the position.
- Include academic transcripts.
- Apply online via the TU Delft application portal.
Note: Applications sent via email or post will not be processed.
Last Date for Apply
All applications must be submitted by May 20, 2026.
