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protein structural insight with hands‑on ML development: adapting and applying state‑of‑the‑art structure prediction and design frameworks, training/fine‑tuning models, and running scalable computational
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state‑of‑the‑art structure prediction and design frameworks, training/fine‑tuning models, and running scalable computational campaigns. Key responsibilities Design and execute in silico protein and
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colleagues on multi‑omics data integration and analysis. You will also work with AI experts to help implement predictive models that improve guide design and functional genomics workflows. You will join an
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model predictions with biological knowledge and external data sources. Work closely with academic partner groups and the Innovation & Business (I&B) team to align technical development with biological
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, regulatory, or multimodal biological data. Support target and mechanism prioritization by integrating model predictions with biological knowledge and external data sources. Work closely with academic partner
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multi‑omics data. You will also partner with AI experts to integrate predictive models and advanced analytics into omics workflows. You will work in an expanding team led by Dr. Masoomeh Rahimpour
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, that combines diffusion and transformer models, there are clear indications that the analysis of this data can be automated. This will open new avenues in data interpretation and building predictive models
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. Our mission is to move beyond descriptive biology and develop predictive, mechanistic models that connect molecular regulation to cellular and systems-level phenotypes. The Laboratory of Computational
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the rapid transition from AI-driven predictions to experimental validation and workflow optimization. We are seeking an experienced Lab Manager to build, lead, and operate this new Technology & Wet Lab Unit
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. The multi-omics spatial and single-cell modalities from perturbed and regenerating livers form the ideal data stack to pioneer such methods. Predictions coming from these methods will be directly validated