PhD student in computational cancer research

Uppsala University

Application deadline

April 29, 2022

PhD student in computational cancer research

Uppsala University, Department of Immunology, Genetics and Pathology

Uppsala University is a comprehensive research-intensive university with a strong international standing. Our ultimate goal is to conduct education and research of the highest quality and relevance to make a long-term difference in society. Our most important assets are all the individuals whose curiosity and dedication make Uppsala University one of Sweden’s most exciting workplaces. Uppsala University has over 54,000 students, more than 7,500 employees and a turnover of around SEK 8 billion.

The Department of Immunology, Genetics and Pathology at Uppsala University ( has a broad research profile with strong research groups focused on cancer, autoimmune and genetic diseases. A fundamental idea at the department is to stimulate translational research and thereby closer interactions between medical research and health care. Research is presently conducted in the following areas: medical and clinical genetics, clinical immunology, pathology, neuro-oncology, vascular biology, radiation science and molecular tools. Department activities are also integrated with the units for Oncology, Clinical Genetics, Clinical Immunology, Clinical Pathology, and Hospital Physics at Akademiska sjukhuset, Uppsala. The department has teaching assignments in several education programmes, including Master Programmes, at the Faculty of Medicine, and in a number of educations at the Disciplinary Domain of Science and Technology. The department has a yearly turnover of around SEK 420 million, out of which more than half is made up of external funding. The staff amounts to approximately 345 employees, out of which 100 are PhD-students, and there are in total more than 700 affiliated people. 

A Ph.D. position is available for a highly motivated student with an interest in large-scale computational cancer research in the research group led by Professor Sven Nelander at Uppsala University, Department of Immunology, Genetics and Pathology. Our research group uses cross-disciplinary methods to understand how cancer arises, progresses and can be treated. We specifically focus on cancer of the nervous system, a group of diseases where the need for new treatments is urgent. The group’s work is characterized by an interdisciplinary approach, where researchers with computational expertise and experimental focus work together. The group ( has around 15 members and is located at the Rudbeck Laboratory and SciLifeLab, two leading centers in data-driven medical research.

The goal of this Ph.D. project is to develop a new computational methodology to understand and target the differentiation of brain tumor cells, their stem cell and invasive properties. Significant focus is placed on the interpretation and modeling of single cell and multiomics data from patients and experimental models with machine learning and AI methodology. The group has a leading position in this area. The Ph.D. project is supervised by prof Sven Nelander (main supervisor) and prof Rebecka Jörnsten (co-supervisor). 

This PhD position is part of the eSSENCE – SciLifeLab graduate school in data-intensive science. The school addresses the challenge of data-intensive science both from the foundational methodological perspective and from the perspective of data-driven science applications. It is an arena where experts in computational science, data science and data engineering (systems and methodology) work closely together with researchers in (data-driven) sciences, industry and society to accelerate data-intensive scientific discovery. 

eSSENCE is a strategic collaborative research programme in e-science between three Swedish universities with a strong tradition of excellent e-science research: Uppsala University, Lund University and Umeå University. 

SciLifeLab is a leading institution and national research infrastructure with a mandate to enable cutting-edge life sciences research in Sweden, foster international collaborations, and attract and retain knowledge and talent.

The successful candidate will devote most of the time towards his/her research level education. Other service activities within the department, e.g. education and administrative work can be included within the framework of the employment (maximum 20%). The position will be extended with the time devoted to teaching to allow four years of full-time graduate studies. The student is expected to take part in courses and other activities of the graduate school. 

To be admitted to the PhD position, a master’s degree is required (, and for the advertised position it is required that the degree is in bioinformatics, technical biology, computer science, mathematics or similar. A degree in medicine or biology complemented by courses in computer science and mathematics can also be accepted. Experience of working in the Unix / Linux environment and documented experience of working in R, Matlab or Python is a requirement. Proficiency in oral and written English is required. 

Additional qualifications
Basic experience and interest in machine learning and neural networks, bioinformatics, biostatistics and medical research is a merit. Strong merits are also previous research experience (e.g. degree project) in genetic or medical epidemiology and documented experience of large-scale data analyzes. Experience of cancer research or knowledge of tumor biology are also merits for this position. 

Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University’s rules and guidelines.

About the employment
The employment is a temporary position according to the Higher Education Ordinance chapter 5 § 7. Scope of employment 100 %. Starting date as agreed. Placement: Uppsala.

For further information about the position, please contact: 
Sven Nelander,, +46 76 1380123

Please submit your application by 29 April 2022, UFV-PA 2022/867.

Last updated: 2022-03-30

Content Responsible: David Gotthold(