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single‑cell omics, AI machine learning, and translational biology. The role involves collaboration with academic research group(s), with a strong focus on bridging advanced computational methods
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positioning of results for partnerships, licensing, or venture creation. Your profile PhD (or equivalent experience) in Computational Biology, Bioinformatics, Systems Biology, Machine Learning, or a related
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the discipline of bioinformatics, data analysis of large-scale (bio)medical data, applications of artificial intelligence and machine learning. You contribute to high-quality teaching in bachelor and master years
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‑on experience with common machine learning / deep learning frameworks (eg. PyTorch or JAX) applied to biological or structural data. Solid Python programming skills, with experience building maintainable and
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, technical depth, and a strong track record of applied research in Computational Biology, Structural Biology, Protein Engineering, Machine Learning, or a closely related field. Strong understanding and
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are looking for a team player who is open to learn about the newest technologies in single-cell and spatial transcriptomics and flow cytometry. Key Responsibilities Collaborate with PhD students, postdoctoral
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experimental workflows for generating and automating the acquisition of high-quality training datasets for machine learning models. Provide training to students on new technologies, protocols, and best practices