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Field
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of results and preparation of high-quality scientific publications within an interdisciplinary project combining forest genomics, evolutionary ecology and forest disturbance ecology. Applicants should have: a
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postdoctoral researcher with a solid background in one or more of the following areas: game theory, optimization algorithms, and numerical methods. The successful candidate will develop efficient algorithms and
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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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, 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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-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
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models. However, rigorous methods for evaluating XAI algorithms are currently lacking. This is in large part due to a gap between how explainability is evaluated within computer science and philosophy. In
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Rossier RG at INL. Job Duties The job duties will be the following: Analog quantum algorithms for quantum search and optimisation based on quantum Hamiltonian evolution. Quantum algorithms for simulation
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have the opportunity to learn to: Understand viral evolutionary biology and mechanisms of pathogenesis Evaluate host–pathogen interactions, immune modulation, and ruminant immunology Conduct