PhD student in Multimodal machine learning for precision medicine

Are you interested in developing new machine learning methods for multimodal data and using these for precision diagnostic of breast cancer, with the support of competent and friendly colleagues in an international environment? Are you looking for an employer that invests in sustainable employeeship and offers safe, favourable working conditions? We welcome you to apply for a PhD position at the Department of Information Technology, 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, with 350 employees, including 120 teachers and 120 PhD students. Approximately 5,000 undergraduate students take one or more courses at the department each year. You can find more information about us on the Department of Information Technology website.

At the Division of Systems and Control, we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and network science, spanning diverse application domains such as energy systems, biomedical systems, material science, and safety and security. We have a wide network of strong international collaborators all around the world, and strive for all PhD students to get a solid international experience during their PhD.

This position is supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP). WASP is Sweden’s largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish society and industry.

Project description
This PhD project is part of the interdisciplinary WASP-DDLS NEST project AID4BC, which has the overarching aim of advancing data-driven multimodal methods to enable true precision diagnostics throughout the breast cancer pathway.  AID4BC’s constellation of partners, located at four leading sites in Sweden, is likely the only constellation globally having access to large (>10,000 patients) matched multimodal data across radiology, pathology and molecular profiling and clinical data.

The focus of this position is on developing methodology for multimodal machine learning, combining large-scale image data with molecular profiling and clinical data. This includes, for instance, research on deep learning-based image analysis and data assimilation methods that update model trajectories over time based on partial, longitudinal, data. The exact details of the project will, however, be decided in a dialogue between the student and supervisor.

The candidate is expected to collaborate extensively with clinical experts at the other sites, with the ultimately goal of uncovering mechanisms underlying breast cancer and translating these insights into precision diagnostics and treatments that improve patient outcomes.

Duties 
The doctoral student will primarily devote their time to graduate education. Other departmental duties of at most 20%, including teaching and administration, may also be included in the employment.

Requirements 
Entry requirements for doctoral education are regulated in the Higher Education Ordinance. To meet the general entry requirements for doctoral studies, you must: 

• hold a Master’s (second-cycle) degree in engineering physics, electrical engineering, machine learning, data science, computer vision, computer science, applied mathematics or in a similar field, or
• have completed at least 240 credits in higher education, with at least 60 credits at Master’s level including an independent project worth at least 15 credits, or
• have acquired substantially equivalent knowledge in some other way.

The University may permit an exemption from the general entry requirements for an individual applicant, if there are special grounds (Chapter 7, § 39 of the Higher Education Ordinance). For special entry requirements, please see the subject’s general study plan. 

We are looking for candidates with

• a solid mathematical foundation and strong interest in developing new machine learning methodology,
• an interest in interdisciplinary collaboration and willingness to translate new methods into clinical applications,
• excellent study results,
• high proficiency in programming (preferably in Python),
• good communication skills with sufficient proficiency in oral and written English,
• personal characteristics such as a high level of creativity, thoroughness, and a structured approach to problem-solving.

Additional qualifications 
Coursework or other experiences with the following subjects are valued: scientific computing, optimization, statistical machine learning, automatic control, computer vision, deep learning, and software engineering.

Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University's rules and guidelines.

Application
The application must contain:

1. A cover letter (max 2 pages), in English, briefly describing your motivation for applying for this position and the earliest possible employment date. The cover letter should include the heading Suitability for this position, containing a self-assessment on why you would be the right candidate for this position.
2. A curriculum vitae (CV).
3. A copy of relevant grade documents (translated into Swedish or English).
4. The Master’s thesis (or a draft thereof, and/or some other self-produced technical or scientific text), publications, and other relevant documents.
5. Contact information for two references (names, emails and telephone number) and up to two letters of recommendation.

About the employment
The employment is a temporary position according to the Higher Education Ordinance chapter 5 § 7. Scope of employment 100 %. Starting date January 12, 2026 or as agreed. Placement: Uppsala.

For further information about the position, please contact: Jens Sjölund, jens.sjolund@it.uu.se, or Dave Zachariah, dave.zachariah@it.uu.se.

Please submit your application by October 15, 2025, UFV-PA 2025/2626.

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