Uppsala University
1 week ago
PhD student in Machine Learning and Uncertainty Quantification for Clinical Cancer Data Uppsala University in Sweden
Degree Level
PhD
Field of study
Computer Science
Funding
Temporary PhD employment at 100% scope under the Higher Education Ordinance, with up to 20% departmental duties such as teaching and administration. The post is part of the DDLS program; no stipend amount is stated.
Deadline
Oct 16, 2026
Country
Sweden
University
Uppsala University
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About this position
Uppsala University, Department of Information Technology, is advertising a PhD position in Machine Learning with a focus on mathematical and statistical methods for uncertainty quantification. The project is based at the Division of Systems and Control and is connected to the national DDLS programme (Data-Driven Life Science) and SciLifeLab.
The research topic combines probability theory, statistics, mathematical modelling, Bayesian statistics, and statistical machine learning. The successful candidate will develop new methods for uncertainty quantification in mathematical and statistical models and apply them to large-scale clinical cancer data. A central application is quantifying uncertainty in information extracted from medical reports and propagating it into downstream probabilistic time-to-event models.
This is a PhD opening in Sweden, with employment at 100% and a temporary position under the Higher Education Ordinance. The post may include up to 20% departmental duties such as teaching and administration. The placement is in Uppsala.
Eligibility highlights: a Master’s degree in applied mathematics, applied statistics, engineering physics, physics, machine learning, or a similar subject; or equivalent higher-education credits/knowledge. Applicants should have strong foundations in linear algebra, probability theory, and calculus, solid programming skills, strong English communication, and a structured, creative approach to problem-solving.
Application materials: one-page cover letter, CV, degree certificates and transcripts, thesis or draft and other relevant documents, and references with contact details plus up to two reference letters. The deadline is 2026-10-16.
Contact person: Assistant Professor Sara Hamis ([email protected]). Apply through Uppsala University’s recruitment system via the SciLifeLab career page.
Funding details
Temporary PhD employment at 100% scope under the Higher Education Ordinance, with up to 20% departmental duties such as teaching and administration. The post is part of the DDLS program; no stipend amount is stated.
What's required
Applicants must meet the general entry requirements for doctoral studies by holding a Master’s degree in applied mathematics, applied statistics, engineering physics, physics, machine learning, or a similar subject; or having completed at least 240 higher-education credits with at least 60 credits at Master’s level including an independent project worth at least 15 credits; or having acquired substantially equivalent knowledge. Required qualifications include strong foundations in linear algebra, probability theory, and calculus; solid programming skills; interest in mathematical and statistical method development; good oral and written English; creativity, thoroughness, and a structured approach to problem-solving. Meriting experience includes Bayesian statistics, mathematical modelling, and statistical machine learning.
How to apply
Prepare a one-page cover letter, CV, degree certificates and transcripts, thesis or draft and other relevant documents, and references with contact details plus up to two reference letters. Submit the application through Uppsala University’s recruitment system before the deadline.
More information can be found here
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