ERC-Funded Postdoctoral Position in Computational Biology Full-time NEW

ERC-Funded Postdoctoral Position in Computational Biology

The Department of Immunology, Genetics and Pathology at Uppsala University has a broad research profile with strong research groups focusing on cancer, genetic and autoimmune diseases. A fundamental idea at the department is to stimulate translational research and thereby promote closer interactions between medical research and health care. Research is presently organized in six research programs: Cancer Precision Medicine, Cancer Immunotherapy, Genomics and Neurobiology, Molecular Tools and Functional Genomics, Neuro-Oncology and Neurodegeneration and Vascular Biology. Departmental activities are also integrated with the units for Oncology, Clinical Genetics, Clinical Immunology, Clinical Pathology, and Hospital Physics at Uppsala University Hospital. The department has teaching assignments in several education programs, including Master Programs, at the Faculty of Medicine. The department has a yearly turnover of around SEK 550 million, out of which about two thirds derive from external funding. IGP has approximately 400 employees, out of which 100 are PhD-students, and there are in total more than 850 affiliated staff members.

The Xingqi Chen Lab at the Department of Immunology, Genetics and Pathology, invites applications for a Postdoctoral Research Associate / Postdoctoral Fellow in computational biology. Our lab develops novel single-cell and spatial biology technologies and applies them to clinically relevant human samples. This position is fully funded by a European Research Council (ERC) grant and focuses on the development of a new computational analysis package for single-cell and spatial multi-omics data.

Research Scope The successful candidate will play a leading role in developing computational and statistical methods for single-cell RNA-seq, single-cell ATAC-seq, spatial transcriptomics, and other high-dimensional spatial biology technologies. The research will be closely integrated with technology development and clinical applications, offering opportunities for high-impact, translational research.

Duties – Lead and drive an ERC-funded research project – Design, implement, and maintain a computational software package for single-cell and spatial biology – Develop robust and scalable computational and statistical methods for high-dimensional data analysis – Analyse and interpret complex datasets derived from clinical samples – Work collaboratively with experimental scientists, clinicians, and engineers – Supervise and mentor postgraduate and undergraduate students – Publish research in high-quality peer-reviewed journals and contribute to project reporting

What We Offer – ERC-Funded Stability: A well-supported postdoctoral position with secure funding – State-of-the-Art Research: Method development at the forefront of single-cell and spatial biology – Rich Clinical Data: Access to unique, large-scale single-cell and spatial datasets – Strong Computational Infrastructure: High-performance computing resources and software support – Career Development: Active mentorship, publication support, and guidance towards independent funding – Leadership Opportunities: Supervision of students and ownership of a major research project – Competitive Salary & Benefits: In accordance with institutional and ERC guidelines

Requirements – PhD in Computational Biology, Bioinformatics, Biostatistics, Biomedical Engineering, or a related quantitative discipline or a foreign degree equivalent to a PhD degree in the same. 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. -Strong computational and programming skills (e.g. Python and/or R) – Demonstrated experience with single-cell and/or spatial omics data analysis – Solid foundation in statistics and high-dimensional data analysis – Evidence of research excellence through peer-reviewed publications – Ability to work independently and as part of a multidisciplinary team

Additional qualifications – Experience developing and maintaining computational tools or software packages – Familiarity with spatial biology technologies and workflows – Experience working with clinical or translational datasets – Prior experience supervising or mentoring students

About the employment The employment is a temporary position of 2 years according to central collective agreement with the possibility of 1 year extension Full time position. Starting date as agreed. Placement: Uppsala

For further information about the position, please contact: Xingqi Chen, xingqi.chen@igp.uu.se