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candidate will join the Scientific Machine Learning group at TDB and SciLifeLab. The group develops theory, methods and software for data-driven science, with a current focus on uncertainty quantification
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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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) to help shape and accelerate the adoption of advanced machine learning and AI in data-driven Life Science research. At the SciLifeLab Bioinformatics Platform (NBIS), a unique national infrastructure with
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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Bioinformaticians in advanced Machine Learning and AI The Department of Biochemistry and Biophysics. SciLifeLab (SciLifeLab ) is a national center for molecular biosciences with focus on health and
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measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with modern deep learning frameworks (PyTorch, JAX, or equivalent). Have
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computational methods with a particular focus on deep learning and image analysis. The project relies on a close collaboration with researchers at the Department of Immunology, Genetics and Pathology (IGP
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modern deep learning frameworks (PyTorch, JAX, or equivalent). Have good software engineering habits — modular, well-documented, reproducible code. Are comfortable working in interdisciplinary teams and
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constellation of SciLifeLab researchers and infrastructure units. This position is embedded in Avlant Nilsson’s research group at Karolinska Institutet and SciLifeLab. Our lab develops deep learning models
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predictive deep learning models, and physical mechanistic models (thermodynamic and kinetic models etc.). Examples of suitable backgrounds: machine learning, programming, mathematics, physics. You will