ERC-Funded Postdoctoral Position in Computational Biology
Uppsala universitet, Brockport, New York, United States
Offer Description
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. More information about the department's activities can be found here: www.uu.se/en/staff/department/immunology-genetics-and-pathology
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 (https://www.chenlabuppsala.com). 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 obtained by 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.
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.
Please submit your application by 27 February 2026, UFV-PA 2026/67.
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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 (https://www.chenlabuppsala.com). 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 obtained by 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.
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.
Please submit your application by 27 February 2026, UFV-PA 2026/67.
#J-18808-Ljbffr