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Machine Learning group at TDB and SciLifeLab (Associate Professor Prashant Singh), which develops methods and software for simulation-based inference, generative models and robust machine learning, together
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in large pre-trained models (vision-language models), generative models (flow matching, diffusion), simulation-based inference, and robust and active learning. The group has a wide network of
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complex or high-dimensional systems. Experience with physics-informed or constraint-based machine learning (e.g. neural ODEs, energy-based models) Experience with dynamical systems, stochastic processes
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program AlphaCell is a new SciLifeLab initiative aimed at building the first molecular-level computational model of the human cell. The program is led by Jan Ellenberg (Director of SciLifeLab) and Mathias
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and variation. The successful candidate will develop innovative methods and models to advance our understanding of genome evolution and variation. The position is based in the Computational Genomics
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SciLifeLab. The successful candidate will work closely with Avlant Nilsson cancer cell modeling lab and Wei Ouyang’s AICell lab who together will develop the first foundation cell model based on HPA and other
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platform to identify and optimize therapeutic candidates. Our group specializes in developing technologies to assess the multicellular environment within three-dimensional microtumor models. The project
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an outstanding and ambitious postdoctoral researcher in computational biology to pioneer understanding and modeling of tissue architecture using single-cell and spatial transcriptomics data. The focus will be
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collaboration with experimental LNP PhD / PostDoc projects in the Barriga Lab and with M. Carroni at the Cryo EM facility SciLifeLab. Other responsibilities may include teaching, supervision and contributions
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model organisms, their application in conifers remains limited due to challenges associated with tissue structure, nuclei isolation and sensitivity to inhibitory compounds. This project aims to develop