PhD Position in Computerised Image Processing and Machine Learning for Cancer Diagnostics Uppsala University in Sweden

Uppsala University’s Department of Information Technology invites applications for a PhD position focused on developing novel image analysis and machine learning methods for cancer diagnostics and clinical decision support. The department is a leader in research and education, hosting a vibrant international environment with over 350 employees and 120 PhD students. The project is led by Professor Joakim Lindblad within the MIDA (Methods for Image Data Analysis) research group and involves collaboration with the Centre for Image Analysis, the Department of Immunology, Genetics and Pathology (IGP), and SciLifeLab, Sweden’s national infrastructure for life science.

The research aims to advance artificial intelligence (AI) and computerised image processing, leveraging digital microscopy to improve clinical pathology and cancer diagnostics. The project addresses the challenge of training AI models with limited, imprecise, and heterogeneous multimodal data, which is common in healthcare settings. The developed methods will be applied to early cancer detection from cell and tissue samples and to personalized treatment prediction, directly impacting patient care.

The doctoral student will primarily focus on graduate education and research, with up to 20% departmental duties such as teaching and administration. The position offers a fixed salary, full-time employment, and is governed by the Higher Education Ordinance. The starting date is 1 September 2026 or as agreed, and the position is based in Uppsala.

Applicants must have a Master’s degree (or equivalent) in computer science, image analysis and machine learning, engineering physics, molecular biotechnology engineering, data sciences, applied mathematics, or a related field. Alternatively, candidates may qualify with at least 240 higher education credits, including 60 at Master’s level and an independent project. Specific requirements include at least 90 ECTS credits in relevant subjects such as image processing, computer vision, machine learning, deep learning, neural networks, Python, GPU programming, mathematical modeling, and statistics. Candidates should demonstrate proficiency in Python and deep learning frameworks (PyTorch, TensorFlow), strong communication skills in English, creativity, thoroughness, structured problem-solving, collaborative skills, drive, and independence. Additional qualifications include interest in biomedical research, experience in medical image analysis, programming in JavaScript, Git, LaTeX, Linux, and experience with convolution and transformer neural networks.

The application should include a CV, degree diploma and transcript, Master’s thesis or other scientific text, contact details for at least two references, and a personal letter outlining motivation, earliest start date, and up to three scientific achievements. Reference letters may be included but are not required at the time of application. Applications must be submitted through Uppsala University’s recruitment system by 1 June 2026.

Uppsala University is committed to sustainable employeeship and offers safe, favourable working conditions. The university is a broad research institution with a strong international reputation, aiming to conduct education and research of the highest quality and relevance. The position may be subject to security vetting. For further information, contact Professor Joakim Lindblad at [email protected].

For more details about working at Uppsala University, visit this page. The application portal is available here.