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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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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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, leading and delivering innovative research to characterise and understand the search landscape and algorithm dynamics induced by combining complex optimisation problems and methods. Description of Duties
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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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, evolutionary theory, quantitative genetics, data science, toxicology, and law. Within this project, our group at the CRG focuses on the analysis of bulk and single cell RNA-seq from five different model species
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mathematical modelling tools. Excellent knowledge of programming languages such as R, Python, Julia, etc. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in
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, tailored, complex materials such as advanced polymers or polymeric formulations, catalysts, mechatronic devices and software and algorithms. Design, control and modelling and analyses complement
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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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challenges in neuroscience, healthcare, and computing; and developing machine learning algorithms to analyze large experimental datasets that deepen our understanding of information processing in the brain