Recent technology advancements in spatially guided transcriptomics will accelerate precision medicine initiatives and enhance biological understanding in an unprecedented manner. Are you interested to learn and contribute to improved understanding of the human tumour immune microenvironment (TIME) by applying and developing novel bioinformatic methods? Two postdoc positions are available within this research area in the CancerTarget group.
Spatial omics has become an essential tool for understanding communication between cells in the TIME and spatial transcriptomics was crowned Method of the Year 2020 by Nature Methods. Deep understanding of cell-to-cell communication is pivotal for progress of cancer research, as most modern treatment approaches target such interactions in the TIME. Spatial transcriptomics allows for highly parallel investigations of the proteome and transcriptome of specific cell types in intact tissue. Sweden is well positioned with high-quality patient samples coupled to information from national patient registers, which constitute a major opportunity for scientific breakthroughs in medical research. Translational research addressing these questions is a multidisciplinary effort that require close collaboration between different actors and professions. Thus, clinicians, pathologists, pre-clinical researchers, technical experts, and bioinformaticians share information that collectively explain the connection between molecular traits and patient outcome.
Examples of questions addressed by the research group are:
- Investigation and characterisation of the heterogeneity of immune infiltration in lung cancer. The study aims to explain the variable response to PD-L1 inhibition and suggest novel therapeutic approaches to increase response rates.
- Characterisation of spatial niches and identification of therapeutic targets in ovarian cancer tumours of different histological subtypes, through parallel investigations of immune and tumour cells.
- Investigation of the impact of distance between macrophages, T-cell subsets and tumour cells on the functionality of cells and patient outcome in B-cell lymphomas
We are seeking two postdocs with bioinformatics expertise for spatial omics analyses and integration with clinical, molecular and imaging data. Bioinformatic workflows will be developed in R and Python, for statistical and image analysis and visualization. The purpose is to establish immune infiltration heterogeneity and activity in relation to tumour types and patient survival and generate prediction models for patient stratification by spatial TIME profiles, as a step towards improved precision medicine. To ensure success of specific postdoc projects, the candidates will be supported by multidisciplinary project teams, experienced in translational research and multiomic data analysis, in a research environment with strong bioinformatics profile.
PhD in bioinformatics, immunology, cancer biology or similar. Experience in bioinformatics including R and/or Python is a requirement. Experience in image analyses, spatial omics-related technologies and/or handling of large patient datasets is a merit.
Partners: Clinical oncologists and pathologists at Skåne University Hospital, Sahlgrenska University Hospital, Uppsala University Hospital and the Nordic lymphoma group. http://www.nordic-lymphoma.org/