PhD student in machine learning
Please note that this is a shortened version of the advertisement. To see the full advertisement, please click "Apply here" or see Uppsala University's website for job advertisements: https://www.uu.se/om-uu/jobba-hos-oss/lediga-jobb
Are you interested in developing mathematically sound methods for uncertainty quantification within deep learning, with a particular focus on large language models for applications in healthcare? Do you want an employer that invests in sustainable employment and offers secure, beneficial working conditions? Welcome to apply for a doctoral student position at Uppsala University.
The Department of Information Technology holds a leading position in both research and education at all levels. We are currently Uppsala University's third largest department and have over 350 employees, including 120 teachers and 120 doctoral students. Approximately 5,000 undergraduate students take one or more courses at the department every year. More information about us can be found on the Department of Information Technology's website.
About the DDLS research program
The doctoral position is part of the national research program DDLS.
Data-driven life science (DDLS) uses data, computational methods, and artificial intelligence to study biological systems and processes at all levels – from molecular structures and cellular processes to human health and global ecosystems. SciLifeLab and the Wallenberg National Program for Data-Driven Life Science (DDLS) aim to recruit and train the next generation of data-driven life science researchers as well as to create globally leading expertise in computational and data science in Sweden. The program is funded with a total of 3.3 billion SEK over 12 years from the Knut and Alice Wallenberg Foundation (KAW).
In 2026, the DDLS research school will be expanded through the recruitment of 25 academic and 7 industrial doctoral students. During the program, more than 260 doctoral students and 200 postdocs will be part of the research school. The DDLS program has four strategic research areas: cell and molecular biology, evolution and biological diversity, precision medicine and diagnostics, and epidemiology and infection biology. For more information, see: https://www.scilifelab.se/data-driven/ddls-research-school/
The future of life science is data-driven. Do you want to be part of that change? Then you are welcome to participate in this unique program!
Project description
Large language models (LLMs) enable the extraction of clinical information from unstructured medical text. However, current LLM-based methods often lack principled uncertainty quantification, which limits their reliability in healthcare applications. The project aims to develop mathematically grounded methods for uncertainty quantification within deep learning, with a particular focus on large language models, where the methods are based on probability theory, statistical inference, and probabilistic modeling. The focus is on quantifying and evaluating uncertainty in predictions derived from medical records and integrating these uncertainties into subsequent probabilistic time-to-event models. The applications will focus on prostate cancer and use large-scale clinical registry data as well as unstructured medical text.
Duties
The doctoral student will primarily devote themselves to their own research training. Other duties at the department, involving teaching and administrative work, may be included within the scope of employment (max 20%).
Qualification requirements
Eligible for education at the doctoral level is the person who has:
a degree at an advanced level in applied mathematics, applied statistics, engineering physics, physics, machine learning, or within a similar field, or completed at least 240 higher education credits, of which at least 60 higher education credits are at an advanced level including an independent project of at least 15 higher education credits, or in some other way acquired substantially equivalent knowledge.
The university may, for an individual applicant, grant an exemption from the requirement of basic eligibility if there are special reasons. (Chapter 7, Section 39 of the Higher Education Ordinance). For specific eligibility, see the syllabus for the subject.
We are looking for candidates with:
an interest in method development within applied mathematics and statistics, an interest in uncertainty-aware machine learning, good communication skills and sufficient knowledge of English in speech and writing, creativity, precision, and a structured approach to problem-solving.
Strong knowledge of linear algebra, probability theory, and analysis is a requirement. Good programming skills are also a requirement.
Other desirable/meritorious qualifications
Experience in one or more of the following areas is meritorious:
Bayesian statistics mathematical modeling probabilistic machine learning deep learning large language models
Provisions for doctoral students can be found in the Higher Education Ordinance Chapter 5, Sections 1-7, as well as in the university's rules and guidelines.
Application
The application must include:
a personal letter (maximum 1 page) explaining how you meet the qualification requirements, motivating why you are applying for this position, and your estimated earliest start date; a curriculum vitae (CV); degree certificates and transcripts of records (translated into English or Swedish); a thesis report (or a draft of one, and/or other self-produced technical or scientific text), publications, and other relevant documents; references with contact information (name, e-mail, and telephone number) and up to two letters of recommendation.
About the employment
The employment is fixed-term, according to the Higher Education Ordinance Chapter 5, Section 7. The scope is full-time. Commencement on October 1, 2026, or by agreement. Location: Uppsala.
Information about the employment is provided by: Assistant University Lecturer Sara Hamis, e-mail: sara.hamis@it.uu.se.
Welcome with your application no later than July 31, 2026, UFV-PA 2026/1935.