Computational Research Engineer in Statistics and Machine Learning

Updated: 20 days ago
Deadline: 25 Jun 2024

Published: 2024-06-10

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: cancer precision medicine, cancer immunotherapy, genomics and neurobiology, molecular tools and functional genomics, neuro-oncology and neurodegeneration and vascular biology. 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 at the Disciplinary Domain of Science and Technology. The department has a yearly turnover of around SEK 500 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. Feel free to read more about the department's activities here:

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. 

Responsibilities may include:

  • 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.


  • MSc degree in applied mathematics, computer science, or related discipline required.
  • Prior experience with Bayesian inference, network inference, variational autoencoders, spatial modeling, 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 team environment required.
  • The degree needs to be obtained by the time of the decision of employment. 

Additional qualifications
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, [email protected]

Please submit your application by June 25th 2024, UFV-PA 2024/1878.

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Uppsala University is a broad research university with a strong international position. The ultimate goal is to conduct education and research of the highest quality and relevance to make a difference in society. Our most important asset is all of our 7,600 employees and 53,000 students who, with curiosity and commitment, make Uppsala University one of Sweden’s most exciting workplaces.

Read more about our benefits and what it is like to work at Uppsala University

The position may be subject to security vetting. If security vetting is conducted, the applicant must pass the vetting process to be eligible for employment.

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Submit your application through Uppsala University's recruitment system.

Placement: Department of Immunology, Genetics and Pathology

Type of employment: Full time , Temporary position

Pay: Individual salary

Number of positions: 1

Working hours: 100%

Town: Uppsala

County: Uppsala län

Country: Sweden

Union representative: Seko Universitetsklubben [email protected]
ST/TCO [email protected]
Saco-rådet [email protected]

Number of reference: UFV-PA 2024/1878

Last application date: 2024-06-25

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