1-2 Postdoctoral Researchers in Bioinformatics or Data Science

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, and the Faculty of Science and Technology. 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

Duties
We are looking for a postdoctoral researcher in Computational Biology, Bioinformatics or Data Science. The research group is connected to SciLifeLab and is part of the National Program for Data-driven Life Science (DDLS), generously funded by the Knut and Alice Wallenberg Foundation. The candidate will work in the lab of Marcel Tarbier (https://www.scilifelab.se/researchers/marcel-tarbier/). Our research is focused on computational method development (statistical approaches and machine learning) for single-cell gene expression data (such as single-cell RNA-sequencing, spatial transcriptomics and in situ sequencing) to infer complex cell features. The two main projects the candidate will work in aim to infer cellular lineage relationships and cellular micro-environments respectively. This is achieved through a data-driven approach, where large complex datasets are quantitatively dissected and subtle signatures are linked to additional observations. This in turn lays the basis for applications in precision medicine related to human biopsies and cancer heterogeneity. The candidate will have the opportunity to individually drive the project forward and develop their own line of research as well as to extent their skills at the intersection of mathematics, programming and biology.

Requirements

PhD degree in computational biology, bioinformatics, biostatistics, data science, applied statistics, machine learning, biotechnology, molecular biology/medicine or quivalent or a foreign degree equivalent to a PhD degree. The degree needs to be obtained by the time of the decision of employment. Those who have obtained a PhD degree three years prior to the application deadline are primarily considered for the employment. The starting point of the three-year frame period is the application deadline. 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.
Skills at the intersection of mathematics, programming and biology are required. The applicant should have experience in two of these fields and an interest in learning about the remaining one.
The candidate is required to possess a strong command of R or python programming as well as experience in the development of original code and algorithms for data analysis. Experience in statistics, handling of big datasets (quantitative, 100s of features, 100s of objects), data analysis and visualization is expected. Fluency in written and spoken English is necessary.

Additional qualifications
Any of the following skills is considered a merit.
· Experience with single-cell RNA-sequencing, spatial transcriptomics or in situ sequencing
· Experience in handling technical and other biases in the data and in handling complex data with interdependent features
· Experience with HPC, parallelization and handling of large datasets
· Experience in feature inference (e.g., inferring an unobserved external factor through its footprint in the data, i.e., transcription factor activity from RNA-sequencing data)
· Experience in multi-omics integration, machine learning or RNA pseudo-time and velocity analyses

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

For further information about the position, please contact: Marcel Tarbier, marcel.tarbier@igp.uu.se

Please submit your application by 14 March 2025, UFV-PA 2025/357.

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