Doctoral Student in Computational Image Analysis

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Are you interested in developing new methods for image analysis and machine learning for precision medicine and clinical decision support? Do you want to be part of a research team with skilled and inspiring colleagues in an international environment? Are you looking for an employer that offers secure and favorable working conditions? Welcome to apply for a doctoral 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 over 350 employees, of whom 120 are teachers and 120 are doctoral students. Approximately 5,000 undergraduate students take one or more courses at the department each year. More information about us can be found on the department's website. The project is led by Professor Nataša Sladoje, within the research group MIDA – Methods for Image Data Analysis – at the Department of Information Technology and is conducted together with other researchers at the Centre for Image Analysis who develop computational methods with a particular focus on deep learning and image analysis. The project builds on close collaboration with researchers at the Department of Immunology, Genetics and Pathology (IGP) at Uppsala University as well as SciLifeLab, the national infrastructure for life science. Project Description Immunotherapy has become a life-saving option for patients with advanced cancer. However, only a minority of patients develop a sustained response. Many researchers are working to better understand the complexity of anti-cancer immunity and develop diagnostic methods that accurately predict treatment benefit and enable personalized cancer treatment planning. Modern AI-based methods are essential to advance this research frontier. This project is an important part of our broader initiative to develop and apply innovative, interpretable data-driven analysis methods to significantly increase our understanding of how immune cell interactions affect the cancer microenvironment. We will apply these analysis methods to high-information multimodal microscopy data and develop techniques to integrate correlated structural and molecular analysis in three-dimensional tissue space. This integration will enable improved prediction of disease progression and response to specific treatments. Duties The doctoral student will primarily focus on their own research training. Other work at the department, including teaching and administrative duties, may be included within the scope of employment (max 20%). Qualification Requirements Basic eligibility is held by those who: have completed a degree at advanced level in computer science, image analysis and machine learning, technical physics, data analysis, applied mathematics, molecular biotechnology, or a related field, or have completed at least 240 higher education credits, of which at least 60 at advanced level including an independent work of at least 15 higher education credits, or have acquired equivalent knowledge in some other way within or outside the country. The university may grant an exception from the requirement of basic eligibility for an individual applicant if there are special reasons. (7 ch. 39 § HF). For specific eligibility requirements, see the curriculum for the subject. Specific requirements are met by having completed courses in areas relevant to image analysis and machine learning, covering at least 90 higher education credits. Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural networks, as well as courses in Python, GPU programming, mathematical modeling, and statistics or equivalent. We seek candidates with: A strong academic background and solid understanding of computation and analysis; Good knowledge of Python programming and deep learning frameworks such as PyTorch and TensorFlow; Excellent communication skills in both spoken and written English; Creativity, thoroughness, and a structured approach to problem-solving; Good collaboration skills, drive, and independence. Desirable/Meriting Additional Qualifications Meriting qualifications include: Interest in biomedical research and experience applying image analysis in medicine; Experience with version control using Git, typesetting with LaTeX, and using Linux computers; Experience with convolutional and transformer-based neural networks for image analysis; Experience with graph-based methods and graph neural networks; Experience with explainable and interpretable AI (XAI). Provisioning for doctoral students is found in the Higher Education Ordinance 5 ch §§ 1-7 and in the university's rules and guidelines. Application The application must contain: Curriculum vitae (CV); Copy of degree/diploma and transcript of course record with grades; Thesis work (or a draft of this, and/or other self-produced technical or scientific text), scientific publications, and other relevant documents in electronic format; Contact information (name, email addresses, and phone numbers) of at least two references, with indication of the context, duration, and nature of the relationship to the candidate. Reference letters may be enclosed as supporting documents but are not required at the time of application. A personal letter (maximum one page) that includes: Your motivation for applying for this position; A short bullet list of three main academic or scientific achievements; Earliest possible start date (with reasons if applicable). About the Position The position is temporary, according to HF 5 ch § 7. The scope is full-time. Start date: 1 October 2026 or by agreement. Work location: Uppsala Information about the position is provided by: Prof. Nataša Sladoje (email: [email protected]). Welcome to submit your application by 20 August 2026, UFV-PA 2026/2366.Are you interested in developing new methods for image analysis and machine learning for precision medicine and clinical decision support? Do you want to be part of a research team with skilled and inspiring colleagues in an international environment? Are you looking for an employer that offers secure and favorable working conditions? Welcome to apply for a doctoral 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…

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Typ

job

Stav

active

Viditelnost

public

Město

Uppsala

Adresa

Regementsvägen 10

GPS

59.839570068472, 17.646119822441kopírovatotevřít v ▾

Email

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Zobrazení

11

Publikováno

16. 7. 2026

Upraveno

5. 8. 2026

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