Bioinformatician / Research Software Engineer / Postdoct in Single Cell and Spatial Omics

The TrueScreen Research to Business (R2B) project at the University of Helsinki is seeking a talented and highly motivated Bioinformatician / Research Software Engineer / Postdoctoral Researcher to join our interdisciplinary team advancing the frontiers of cancer research through single-cell and spatial omics technologies. About the position This position offers the opportunity to work at the intersection of computational biology, biotechnology, and precision medicine. You will contribute to the development of innovative bioinformatics tools and perform in-depth analysis of cutting-edge datasets, with direct relevance to improving cancer diagnostics and treatment. Our lab focuses on biomarker discovery and clonal evolution in early-stage cancers, leveraging both computational and experimental techniques. We maintain close ties with clinical collaborators at the University Hospital (HUS) and are part of a vibrant research ecosystem at the University of Helsinki (Erickson Lab). Key Responsibilities - Develop Computational Pipelines for the analysis and integration of spatial transcriptomics, single-cell RNA-seq, and other multi-omics datasets. - Analyze Omics Data at all levels, from preprocessing (QC, normalization, dimensionality reduction) to downstream interpretation (differential expression, gene set enrichment, and cell type annotation). - Implement Machine Learning Approaches, including deep learning techniques, for multimodal data analysis and integration with histopathological images and transcriptomic data. - Ensure Reproducibility and Scalability by managing and maintaining robust data analysis workflows on high-performance computing (HPC) systems. - Closely Collaborate with Clinicians and Wet-Lab Scientists on the experimental design and collect data for computational modelling and analysis. - Engage Actively with the Research Community, participating in lab meetings, seminars, and collaborative projects, and supporting the development of shared infrastructure. Candidate Requirements Essential: - Proficiency in Python, R, and Linux shell scripting. - Hands-on experience with HPC environments, workflow management systems, and job schedulers. - Expertise in machine learning and its application to biological data. - Strong communication skills and the ability to explain complex concepts to diverse audiences. - A Master's degree (or PhD) in Bioinformatics, Computational Biology, Computer Science, or a related field. Desirable: - Previous experience with single-cell or spatial transcriptomics data, particularly in urological cancers (e.g., prostate, bladder, or kidney cancer). - Experience in image analysis, digital pathology, or multimodal data integration.

The Faculty of Medicine promotes high quality scientific research. It provides research-based undergraduate and postgraduate education in medicine, dentistry, psychology and logopedics, and an international Master's Programme in Translational Medicine. It also offers psychotherapist education. In addition to its teaching and research activities, the faculty serves as a significant expert organisation in the healthcare sector and contributes to the discourse on ethics in the field. The faculty aims to be one of the best medical research faculties in the world, while reinforcing its status as a distinguished institution of multidisciplinary education in healthcare.