Postdoctoral position in Computerised Image Processing with focus on Machine Learning for Data-Driven Precision Medicine and Diagnostics Full-time NEW

Postdoctoral Position in Computerised Image Processing with Focus on Machine Learning for Data-Driven Precision Medicine and Diagnostics

Are you interested in developing new image analysis and machine learning methods for cancer diagnostics and clinical decision support? Would you like to work in a multidisciplinary team together with 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 postdoctoral research 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. The project is led by Professor Joakim Lindblad, 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 a close collaboration with researchers at the Department of Immunology, Genetics and Pathology (IGP) at Uppsala University and SciLifeLab, the national infrastructure for life science.

The development of artificial intelligence (AI) and computerised image processing in combination with advanced digital microscopy is enabling major advances in clinical pathology and cancer diagnostics. Today's AI methods require large amounts of data with a detailed ground truth annotation that the AI system can learn from. In healthcare, in most cases, there is only access to information at the patient level, about the patient's health status and disease development. In this project, we will develop theory, algorithms and methods to effectively train AI models based on limited and imprecise information as well as unbalanced and heterogeneous multimodal data.

This needs-driven method development finds direct application in healthcare. Together with our partners in healthcare and biomedicine, we will apply the developed methods to detect cancer from cell and tissue samples as early as possible and to individually predict which treatment is expected to give the best result for the patient.

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.

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.

Meriting is:

• Interest in biomedical research and experience in application of image analysis in medicine.
• Experience of programming in JavaScript, software version control with Git, typesetting with LaTeX, use of Linux computers;
• Experience with convolutional and transformer-based neural networks for image analysis;
• 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.

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 documents but are not required at the time of the application.
6. A personal letter (max 1 page) which includes:
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 activities;
4. The earliest possible starting date of employment.

The employment is a temporary position of 2 years according to central collective agreement. Full time position. Starting date 1 September 2026 or as agreed. Placement: Uppsala.

For further information about the position, please contact: Prof. Joakim Lindblad (e-mail: joakim.lindblad@it.uu.se)

Please submit your application by 1 June 2026, UFV-PA 2026/1409.