PhD Student in Computational Biology / Bioinformatics

The Department of Immunology, Genetics and Pathology at Uppsala University has a broad research profile with strong research groups focused on, among other things, cancer, autoimmune and genetic diseases. One of the core ideas at the department is to stimulate translational research and thus a closer collaboration between medical research and healthcare. Research is conducted in cancer precision medicine, cancer immunotherapy, genomics and neurobiology, molecular tools and functional genomics, neuro-oncology and neurodegeneration, as well as vascular biology. Parts of the activities are also integrated with the departments of oncology, clinical genetics, clinical immunology, clinical pathology, and hospital physics at Uppsala University Hospital. The department has teaching assignments in several program courses, independent courses, and international master's programs within the medical faculty. The department has a turnover of approximately 500 million SEK, of which just over half is external research grants. The number of employees is about 345, of which about 100 are PhD students, and there are a total of over 700 active in the workforce. Please read more about the department's activities here: https://www.uu.se/institution/immunologi-genetik-och-patologi (https://www.uu.se/institution/immunologi-genetik-och-patologi)

Do you want to work on the development of computational methods for data on gene expression from single cells (specifically for cell lineage relationships), supported by competent and friendly colleagues in an international environment? Do you want an employer that invests in sustainable employee engagement and offers secure, favorable working conditions? Welcome to apply for a PhD position in computational biology / bioinformatics at Uppsala University.

The laboratory's research focuses on the development of computational methods (statistical methods and machine learning) for data on single-cell gene expression (such as single-cell RNA sequencing, spatial transcriptomics, and in situ sequencing/sequential FISH) to derive complex cell characteristics. The research group is linked to the Science for Life Laboratory (SciLifeLab) and is part of the national program for data-driven life sciences (DDLS).

The central focus of the project is cellular lineage relationships (ancestries), how they can be predicted, and how these predictions can inform trajectories, phenotype switches, and common downstream single-cell analyses.

The candidate will have the opportunity to individually drive projects forward and develop their own research line as well as expand their skills at the intersection of programming, statistics, and biology.

Job Responsibilities

We are looking for a highly motivated person who will test tools for lineage inference (based on CNV, somatic mutations, and gene expression) in ground truth samples as well as healthy and cancerous tissues. You will apply the GEMLI algorithm (https://www.nature.com/articles/s41467-024-47158-y (https://www.nature.com/articles/s41467-024-47158-y)), improve and extend it, and integrate it with other algorithms to obtain a more comprehensive picture of cell lineage relationships. You will apply lineage inference to study lineage-specific gene expression, plasticity, cancer heterogeneity, cell fate decisions, and other lineage-related questions. You will create software, summarize results for scientific publication, and communicate your research to experts and laypeople.

Qualifications

Eligible for doctoral education is someone who has:

• completed a master's degree in computational biology, bioinformatics, or equivalent, or
• completed at least 240 higher education credits, of which at least 60 higher education credits at the advanced level including an independent project of at least 15 higher education credits, or
• acquired equivalent knowledge in some other way.

Skills at the intersection of programming, statistics, and biology are required. The candidate should have good knowledge of R and/or Python programming as well as experience in developing original code for analyzing single-cell transcriptomics data. Experience in advanced statistics, handling large datasets, and data visualization is expected. Fluent written and spoken English is necessary.

Desirable/meritorious

Any of the following skills are considered meritorious:

• Experience in handling technical and other biases in data and in managing complex data with interdependent features
• Experience in HPC, parallelization, and handling large datasets
• Experience in functional inference (e.g., inferring an unobserved external factor through its footprint in data, i.e., transcription factor activity from RNA sequencing data)
• Experience in machine learning, pseudotime, or RNA velocity analyses
• Experience in software development and documentation

Regulations for doctoral students can be found in the Higher Education Ordinance Chapter 5 §§ 1-7 and at https://www.uu.se/medarbetare/organisation-styrning/regler/ (https://www.uu.se/medarbetare/organisation-styrning/regler/)

About the Employment

The employment is temporary, according to HF Chapter 5 § 7. The extent is full-time. Start date by agreement. Place of employment: Uppsala

For inquiries about the position, please contact: Marcel Tarbier, +46737885977, [email protected]

Welcome with your application by December 29, UFV-PA 2025/3243.

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 7,600 employees and 53,000 students who, with curiosity and commitment, make Uppsala University one of the country's most exciting workplaces.

Read more about our benefits and what it is like to work at Uppsala University https://uu.se/om-uu/jobba-hos-oss/ (https://uu.se/om-uu/jobba-hos-oss/)

The employment may be subject to security clearance. For security clearance, a prerequisite for employment is that the applicant is approved.

We kindly decline offers of recruitment and advertising assistance.

Applications are received in Uppsala University's recruitment system.

Union representatives: Saco-S - [email protected], Seko - [email protected], ST (OFR/S) - [email protected]