Joakim Lindblad

Uppsala University invites applications for a funded PhD position in computerised image processing and machine learning, with a focus on data-driven precision medicine and diagnostics. This position is part of the prestigious Data-Driven Life Science (DDLS) national research program, which aims to advance computational and data science capabilities in Sweden and train the next generation of life scientists. The DDLS program is funded by the Knut and Alice Wallenberg Foundation and offers a collaborative, multidisciplinary research environment. The project is led by Professor Joakim Lindblad at the Centre for Image Analysis and the Vi3 division, Department of Information Technology, in close collaboration with researchers at the Department of Immunology, Genetics and Pathology (IGP) and SciLifeLab. The research focuses on developing new theory, algorithms, and methods for training AI models using limited, imprecise, and heterogeneous multimodal data, with direct applications in healthcare. The goal is to improve early cancer detection from cell and tissue samples and to predict optimal treatment strategies for individual patients. As a doctoral student, you will primarily devote your time to graduate education and research, with the possibility of up to 20% departmental duties such as teaching and administration. You will work in a dynamic, international team and benefit from Uppsala University's strong research infrastructure and supportive working conditions. Eligibility: Applicants must hold 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 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. Specific requirements include passing exams in relevant subjects (minimum 90 ECTS credits), such as image processing, computer vision, machine learning, deep learning, neural networks, Python, GPU programming, mathematical modeling, and statistics. Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow), excellent English communication skills, creativity, thoroughness, structured problem-solving, collaborative skills, drive, and independence are essential. 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. Funding: The position is fully funded as part of the DDLS program, with salary and benefits according to Uppsala University regulations. Employment is 100% and temporary, as per the Higher Education Ordinance chapter 5 § 7. The DDLS program is supported by a 3.3 billion SEK grant over 12 years. Application Process: Submit your application online by 22 May 2026. Required documents 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 main scientific achievements. Reference letters are optional at the time of application. For further information, contact Professor Joakim Lindblad ([email protected]). Uppsala University is a broad research university with a strong international reputation, offering a vibrant academic environment and excellent benefits. The Department of Information Technology is one of the largest and most active departments, with extensive research and teaching activities. The DDLS program provides unique opportunities for interdisciplinary collaboration and professional development in data-driven life science. For more information about the DDLS Research School, visit https://www.scilifelab.se/data-driven/ddls-research-school/ . To learn more about working at Uppsala University, see https://uu.se/om-uu/jobba-hos-oss/ . Deadline: 22 May 2026. Starting date: 1 September 2026 or as agreed. Location: Uppsala, Sweden.