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significant computational component. We strongly recommend a background in machine learning and coding. Applicants with a background in areas such as computational neuroscience, reinforcement learning, or deep
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and output databases; deployment of methods and tools for data acquisition and visualization; * AI/Machine Learning/Deep learning techniques for model input and output data analysis and production, in
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. The approach used relies on developing machine-learning interatomic potentials based on ab initio calculations, which are then employed to perform large-scale classical molecular dynamics simulations. However
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computational tools (e.g. machine learning, artificial intelligence or other approaches) are also encouraged to apply. You will teach pharmacology-related courses in the Bachelors of Life Sciences, Medicine
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experimentation with innovative modeling, data analysis and machine learning/AI techniques. 1 - Global Energy-Economy-Environment Systems Modelling Your main duty is to contribute to our collection of linear
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are particularly interested in candidates who combine computational biology, data science, and machine learning/AI with deep biological insight. While wet lab activities are welcome, they are not mandatory. However
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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functions in different neurological disorders Teach students about clinical and research aspects of neurodegenerative disorders Present at public events for information of lay public or medical professionals
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to candidates from a broad range of AI subfields, including, but not limited to machine learning, generative AI, computer vision, representation and reasoning, natural language processing
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly