WASP-PhD Position in Machine Learning: The KTH Royal Institute of Technology invites applications for a fully funded WASP-PhD position in the School of Electrical Engineering and Computer Science. This opportunity is part of a research initiative focused on enhancing the reliability and trustworthiness of machine learning models.
Designation
PhD Student in Probabilistic Machine Learning
Research Area
- Reliability and trustworthiness of machine learning models
- Development of open-source machine learning libraries
- Collaboration with researchers on trustworthy AI
Location
Stockholm County, Sweden
Eligibility/Qualification
To qualify for this position, applicants must have:
- A second cycle degree (master’s degree) or equivalent, with at least 240 higher education credits (60 credits at the second cycle level)
- Strong mathematical and programming skills
- Background in machine learning, statistics, linear algebra, and optimization
- Prior research experience with peer-reviewed publications
- English language proficiency equivalent to English B/6
Job Description
The selected candidate will:
- Work with open-source large-scale machine learning models
- Develop theoretical and methodological approaches to improve model reliability and trustworthiness
- Publish research findings in top-tier machine learning venues (NeurIPS, ICML, ICLR, UAI, AISTATS)
- Collaborate with various researchers and contribute to interdisciplinary projects
How to Apply
Interested candidates should apply through KTH’s recruitment system, ensuring the application includes:
- Copies of diplomas and grades from previous university studies
- CV (maximum 1 page)
- Research statement (maximum 1 page)
- Application letter (maximum 1 page)
- List of publications or technical reports with links
For more details on the application process, please check the official KTH website.
Last Date for Apply
Applications must be submitted by December 19, 2025 at midnight (CET/CEST).
