Summary
The School of Electrical Engineering and Computer Science at KTH offers a scholarship position for a doctoral student focusing on the development of probabilistic and AI-enhanced Bayesian methods to analyze tumor DNA and circulating tumor DNA (ctDNA) to detect metastases. This position involves collaboration with Karolinska Institutet (KI) and access to unique international cancer data.
Doctoral Student in AI and ML for Analysis of Single-Cell Cancer Data, Stockholm, Sweden
Designation
Doctoral Student in AI and ML for Analysis of Single-Cell Cancer Data
| Details | Information |
|---|---|
| Research Area | Data-Driven Life Science (DDLS) |
| Location | Stockholm, Sweden |
| Eligibility/Qualification | Master’s degree or equivalent in areas like computer science, mathematics, bioinformatics, etc. |
| Job Description | Develop methods for analyzing cancer data using machine learning and deep learning approaches. Collaborate with other researchers, analyze complex issues, and work on independent research projects. |
Research Area
Focus on probabilistic analysis, machine learning, Bayesian inference, and phylogenetic modeling in cancer research.
Location
Stockholm, Sweden
Eligibility/Qualification
- A completed Master’s degree or equivalent in:
- Computer Science
- Mathematics
- Statistics
- Bioinformatics
- Related Fields
- English proficiency equivalent to English B/6
Job Description
- Engage in developing AI-enhanced Bayesian methods for analyzing cancer data.
- Collaborate closely with KTH and KI researchers.
- Work on single-cell data and longitudinal studies.
- Contribute to the development of deep learning-based inference methods.
How to Apply
Interested candidates should submit their applications through KTH’s recruitment system, including:
- Diplomas and grade transcripts
- CV highlighting relevant experience
- Application letter (max 2 pages)
- Publications or technical reports (with summaries and links)
Last Date for Apply
The application deadline is June 3, 2026, by midnight CET/CEST.
For more information about the position and to apply, contact Jens Lagergren at jensl@kth.se.
