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Field
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achieved by combining state-of-the-art algorithms from multiple domains such as evolutionary algorithms, reinforcement learning, and control theory. The main responsibility of the successful applicant will
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achieved by combining state-of-the-art algorithms from multiple domains such as evolutionary algorithms, reinforcement learning, and control theory. The main responsibility of the successful applicant will
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to accelerate evaluation of costly simulations Genetic algorithms and other evolutionary techniques to generate a diverse set of high-performing solutions. You will design and implement new optimization
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Missouri University of Science and Technology | Rolla, Missouri | United States | about 15 hours ago
genome-based influenza and/or SARS-CoV-2 risk assessment algorithms, designing broadly protective influenza and SARS-CoV-2 vaccines using Machine Learning and Artificial Intelligence, modeling the impacts
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Responsibilities Computational Modeling & AI Development Train and fine-tune ESM (Evolutionary Scale Modeling) protein language models on curated datasets to generate novel protein sequences Develop and optimize
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both the algorithms for robot co-design, and the real-world evaluation of the designs that emerge. You will investigate evolutionary algorithms to explore creative new hand designs, and reinforcement
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minimizing error and maximizing efficiency, is computationally challenging—no known polynomial-time algorithm exists to solve it optimally in all cases. Because of this complexity, researchers typically rely
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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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needs, such as assisting the team with evaluating evolutionary algorithms for exploring creative new hand designs, or reinforcement learning for policy optimisation, all within a huge GPU-based simulation
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
loss patterns across diverse plant lineages Explore graph-based algorithms for multiple genome alignment and ancestral karyotype reconstruction Position 2: Evolutionary Analysis and Network