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highly motivated researcher to develop artificial intelligence based novel algorithms and computational workflows to predict the impact of mutations on genes in the avian flu virus and the viral host which
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binding pockets. About the role We are seeking a highly motivated researcher to develop artificial intelligence based novel algorithms and computational workflows to identify domain functional families
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grant, have worked to identify the sampling algorithm used by the brain, to show how the identified sampling algorithm can systematically generate classic probabilistic reasoning errors in individuals
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algorithms might support the wider integration of, and uptake of, renewable energy technologies for particular use cases and considering a variety of perspectives (technical/policy/social/economic). You will
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HiPerBreedSim project. In this role, you will leverage recent advances in working with ancestral recombination graphs (ARGs) to develop algorithms and code for simulating population genomic data, including
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include but are not limited to: network architecture design for NTN and terrestrial network (TN) convergence, intelligent traffic steering algorithms between TN and NTN, orchestration of TN/NTN resources
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-fostering prototypes through co-design with children, creating evaluation frameworks to assess children's algorithmic agency in educational contexts, and establishing design principles that prioritize
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to) fundamental research in machine learning or statistics, algorithm design, the application of AI methods in science, healthcare, social sciences, or business. You should have a PhD or equivalent level of
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combining these to explore the possibility of improving outcomes. These algorithms will then be used to develop a prognosis platform. You will investigate different approaches and find novel ways to improve
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compressible mixing, such as supersonic reacting flows relevant to high speed combustion problems and external aerodynamics. We expect that both the developed algorithms and the fundamental physics discovered