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interpretable reduced-order models for fuel cell control using the Sparse Identification of Nonlinear Dynamics (SINDy) algorithm applied to numerical and experimental data. You will work closely with
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Do you think that quantum computing can open genuinely new routes for analysing biological data? Are you excited to work where bioinformatics, molecular modelling and quantum algorithms meet? Join
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workflows into structured representations suitable for AI planning and optimization algorithms. 2) Research Leadership & Mentorship: * Abstract from the practical challenges presented by the work and
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demonstrations. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development. Responsibilities will include programming
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About the Opportunity Conduct research on machine learning, control theory, and synthetic biology. The work will combine tools from dynamical systems, control theory, and the theory of algorithms
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architecture underlying rapid evolutionary shifts in sensory preference, to the neural mechanisms of anatomy–circuit coevolution. Projects integrate molecular genetics, functional neuroscience, quantitative
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substrate – coelenterazine. Even though bioluminescence is a surprisingly common trait in marine organisms, little is known about its ecological, evolutionary and biochemical nature. We will establish
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, comparative genomics, machine learning, and evolutionary analysis to address fundamental questions in molecular biology and human disease. Responsibilities Develop computational pipelines for the discovery
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Experience developing software with Python, R, and/or Julia Experience with machine learning and AI algorithms and tooling (e.g. PyTorch) Experience with remote sensing and open-source GIS tools (e.g. Google
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-driven research group working at the intersection of computational genomics, clinical artificial intelligence, and imaging genetics. This position offers an exciting opportunity to develop novel algorithms