PhD Student in Machine Learning for Uncertainty Quantification in Clinical Cancer Data (Ref. UFV-PA 2026/2836)
Uppsala University, Department of Information Technology · Sweden
Deadline
October 16, 2026 (CET)· 18 days left
Degree Level
PhD
Funding
Fully Funded
Location
On-site
Overview
PhD project developing mathematical and statistical uncertainty-quantification methods for large-scale clinical cancer data, including probabilistic time-to-event modelling. Deadline 16 October 2026; start 15 November 2026 or as agreed.
Eligibility
Master's degree (or 240 credits incl. 60 at Master's level) in applied mathematics, statistics, engineering physics or similar; strong linear algebra, probability, calculus and programming skills.
Nationality: Open to all nationalities
Funding & Benefits
Full-time salaried doctoral position within the national Data-Driven Life Science (DDLS) programme funded by the Knut and Alice Wallenberg Foundation (fixed salary; up to 20% departmental duties).