Bioinformatics / Data Scientist

Role overview Use computational biology and data science to assess organoid models against corresponding normal tissues. The work combines multi-omics analysis with experimental design input, with the aim of characterizing how faithfully organoids reflect tissue biology, identifying markers of successful differentiation, and developing computational approaches to assess organoid quality. You will work closely with experimental teams and share findings through papers and conference presentations.

Responsibilities - Analyze single-cell and bulk RNA sequencing, proteomics, and metabolomics data from organoid systems and corresponding tissues. - Consult with wet-lab collaborators on study design to improve protocols and support useful biological discoveries. - Develop computational workflows for data processing, quality control, and statistical analysis. - Compare internally generated results with public datasets to benchmark organoid profiles against normal tissues. - Interpret results with experimental teams and help guide protocol optimization. - Contribute to manuscript preparation and present research findings at scientific meetings.

Requirements - PhD in bioinformatics, computational biology, biostatistics, or a related quantitative discipline. - Extensive experience analyzing single-cell data, using tools such as Seurat, Scanpy, or comparable platforms. - Strong programming skills in R and Python, including statistical analysis and data visualization. - Basic knowledge of proteomics and metabolomics data.

Nice to have - Experience analyzing organoid datasets. - Familiarity with machine learning for biological data, pathway analysis tools, and developmental biology. - Experience using high-performance computing environments and version control.