Postdoc - Machine learning & statistics for spatial omics data
We are currently looking for a Postdoc to join our group for developing statistical and machine learning methods to identify patterns from spatial omics data.
Spatial omics technologies have transformed research in the life sciences by generating quantitative molecular read-outs with spatial resolution and providing us with new insights into spatial organization and reorganization of tissues in development and disease. In our group we aim to develop the required computational tools to facilitate the analysis of such data. As part of our group you will develop novel probabilistic machine learning approaches and statistical methods to identify spatial patterns from spatially-resolved molecular data sets and model biological heterogeneity across spatial scales ranging from single molecules to tissue level.
Located at the Centre of Organismal Studies (COS) and Center for Scientific Computing (IWR) at Heidelberg University our group provides a great atmosphere for interdisciplinary projects at the interface of machine learning, statistics and life sciences. We invite applications both from quantitative disciplines (incl. mathematics, physics, computer science) interested in biological applications as well as computational biologists with solid experience in computational method development and data analysis.
We are looking for a highly motivated candidate with a strong background in quantitative and analytical research, experience in scientific computing and the curiosity to apply their expertise to address pertinent biological questions in development and disease. Prior experience in probabilistic modelling and machine learning, image analysis, omics data analyses or the analysis of spatial or temporal data are considered a plus. In addition, the candidate should have:
- a degree in a quantitative discipline (incl. mathematics, physics, computer science or computational biology)
- solid programming experience in Python and/or R
Additionally, we expect passion for science, independent thinking, fluency in written and spoken English, interdisciplinary communication skills and the entrepreneurial and team-player spirit for a young and growing research group.
If this fits you, please send a CV, a letter of motivation with your research interests, code samples of previous projects and names of at least 2 references directly to Britta Velten.
No open positions at the moment.
Bachelor and Master students
We are happy to host you for your B.Sc., M.Sc. thesis or an internship in our lab. If you are interested, please contact Britta Velten with your CV, transcripts of record, a short statement outlining your research interests and why you want to join our lab, and the proposed duration of your stay.