Research Engineer in Spatial Computational Models and Machine Learning

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 Vickovic Lab at Uppsala University is seeking a dynamic, self-motivated, team-oriented Associate Computational Biologist or Statistician to expand computational efforts in understanding disease mechanisms. We are interested in developing integrative multi-modal data analysis tools incorporating single cell and spatially resolved omics data, imaging data, clinical phenotypes, variants and genotypes. The successful candidate will have the unique opportunity to work at the intersection of mathematical modeling, omics data analysis, workflow optimization, and resource building.
The Vickovic Lab is focused on developing novel “digital pathology” tools to track disease progression with the aim of identifying translatable drug and therapeutic targets in human tissue cohorts. The team leverages technologies including spatial transcriptomics, single-cell sequencing, and machine learning.

Duties 
- Develop new computational, machine learning, and statistical analysis methods for integrating and analyzing large-scale, spatially resolved RNA-seq and genotypic data using current state of the art technologies.
- Develop data analysis strategies, write algorithms, and deploy computational tools for the exploration of very large data sets.
- Develop a resource for the community that gives access to collected data.
- Work closely with experimental colleagues and cores to understand the nature of generated data.
- Actively participate in the preparation of manuscripts for publication and present at scientific conferences.
- Assist in peer- and student-mentorship.
- Share expertise and provide training and guidance to group members as needed.

Requirements 
- BSc degree in applied mathematics, computer science, or related discipline required.
- Prior experience with network inference, variational autoencoders, spatial modeling, software development, segmentation and image analysis are required, but exceptionally creative and driven scientists with an interest and adaptability will be seriously considered.
- Strong oral and written communication, data documentation, and presentation skills required.
- Experience writing scientific articles for publication required.
- Ability to handle multiple projects at the same time required.
- Excellent collaborative and interpersonal skills, and willingness to work in a fast-paced tea environment required.
- The degree needs to be obtained by the time of the decision of employment. 

Technical and Professional Skills: Consistently demonstrates skills and knowledge relevant for current role; strives to expand the depth and breadth of technical and professional skills; works with a high level of integrity; exhibits focus and discipline; appropriately prioritizes, manages expectations and delivers on commitments.

Collaborative & Communicative: Models collaboration and teamwork; brings out the best in others; effectively works with all levels, internally and externally; respects and embraces diversity of perspective; communicates clearly and listens carefully; uses good judgment as to what to communicate and when to do so.

Adaptable & Innovative: Adaptable and embraces change; develops new insights and pursues improvements and efficiency; fosters exchange of new ideas and willing to challenge the status quo, takes initiative and is solution-oriented; engages in work with passion and curiosity.

About the employment
The employment is a temporary position, 12 months. Scope of employment 100 %. Starting date as agreed. Placement: Uppsala

For further information about the position, please contact: Sanja Vickovic, sanja.vickovic@igp.uu.se

Please submit your application by 7 January 2026, UFV-PA 2025/3666

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