Postdoctoral position in Computerized Image Processing with focus on Applications in data-driven precision medicine

Are you interested in developing new image analysis and machine learning methods for precision medicine and clinical decision support? Would you like to work together with competent and inspiring colleagues in an international environment? Are you seeking an employer that offers safe and favourable working conditions? We welcome you to apply for a postdoctoral research position in Computerized Image Processing for data-driven precision medicine 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, have around 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.

The project will be led by Professor Nataša Sladoje, within the MIDA – Methods for Image Data Analysis – research group at the Department of Information Technology, and will be conducted alongside other researchers at the Centre for image Analysis who develop computational methods with a particular focus on deep learning and image analysis. The project relies on close collaboration with researchers at the Department of Immunology, Genetics and Pathology (IGP) at Uppsala University.

Research project
This project is a key part of our broader initiative to develop and utilize innovative, interpretable data-driven analysis methods to significantly advance our understanding of immune cell inter-relations within the cancer microenvironment. We will apply these analysis methods to highly informative multimodal microscopy data and develop techniques to integrate correlated structural and molecular analysis into the natural 3D tissue space. This integration will advance the ability to predict disease progression and response to specific therapies.

The details of the research direction within the project frame will be decided in a dialogue between the postdoctoral fellow and the supervisor.

Duties
The successful candidate will devote the majority of their time to research.

The duties include method development, implementation, data management, evaluation and analysis, manuscript preparation, as well as own career development. Assisting PhD students in the research group on related research tasks will be a part of the duties. Teaching in related subjects (max 20%), including master student supervision, can also be included depending on availability and interest.

The candidate is expected to take an active role in the MIDA research environment and contribute to the development of the research milieu.

Requirements
PhD degree in a field closely related to the position (e.g., computerized image analysis/processing, machine learning, artificial intelligence, data science, computer science) or a foreign degree equivalent to a PhD degree in a field closely related to the position. The degree needs to be obtained by the time of the decision of employment. Priority will be given to applicants who have completed their degree no more than three years before the deadline for applications. Due to special circumstances, the degree may have been obtained earlier. The three-year period can be extended due to circumstances such as sick leave, parental leave, duties in labour unions, etc.

The candidate must have documented experience in image analysis, machine and deep learning, including completed courses in these fields, at the master and doctoral level of education, as well as first-hand experience in method development, implementation, evaluation, and publication (first author) of scientific articles in internationally recognized journals and presentations at international conferences.

We are looking for candidates with:

• A solid academic background with thorough computational and analytical understanding;
• Proficiency in programming in Python and deep learning frameworks such as PyTorch and TensorFlow;
• Excellent communication skills in oral and written English;
• Creativity, thoroughness, and a structured approach to problem-solving;
• Good collaborative skills, drive, and independence.

Additional qualifications
Meriting are:

• Interest in biomedical research and experience in application of image analysis in medicine.
• Experience of software version control with Git, typesetting with LaTeX, use of Linux computers;
• Experience with graph-based methods, and graph convolutional/neural networks;
• Experience with explainable and interpretable AI (XAI);
• Experience of university level teaching and supervision.

When selecting among the applicants we will assess their ability to independently drive their work forward, to collaborate with others, to have a diligent and professional approach and to analyse and address complex problems. An emphasis will be placed on personal characteristics and personal suitability.

Application
The application should consist of:

1. A Curriculum Vitae (CV);
2. A copy of relevant grade documents (translated into Swedish or English);
3. A list of publications;
4. Up to five selected publications in electronic format;
5. Contact details (names, emails, and telephone numbers) of minimum two references, also specifying the context, duration, and nature of the relationship with the candidate. Reference letters may be provided as supporting document but are not required at the time of the application.
6. A personal letter (max 2 pages) which includes
7. 1. Described motivation for the application for this position;
   2. A list with your up to three main scientific achievements;
   3. A research statement describing your past and current research and a proposal for future activities.
   4. The earliest possible starting date of employment;

About the employment
The employment is a temporary position of 2 years according to central collective agreement. Full time position. Starting date 2026-02-01 or as agreed. Placement: Uppsala

For further information about the position, please contact: Prof. Nataša Sladoje (email: natasa.sladoje@it.uu.se )

Please submit your application by 5 December 2025, UFV-PA 2025/3273.