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developing new algorithmic approaches for TAPS data, interpreting the results in the context of phenotypic observations, and communicating these findings clearly to the broader team. You will prepare the
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recordings, optogenetics, pharmacology and advanced computational tools to analyse neural algorithms, their deficits and their rescue in genetic mouse models. This project is part of a cross-species, cross
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developed goal-sequence generalization task. The project will integrate high-density silicon probe recordings, optogenetics, pharmacology and advanced computational tools to analyse neural algorithms
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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
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microbial communities. In this role, you will develop hybrid species distribution models that combine climate and landscape data to predict how microbial taxa niches shift under changing land use and
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precisely monitor changes in the global distribution of CO₂ sources and sinks. The UK science lead for MicroCarb is at the University of Edinburgh so this opportunity is a valuable opportunity to gain a deep
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-related multimodal processing (audio with text and/or video), audio deep learning, or a related topic. The post holder would have experience in developing new research algorithms or methods, using languages
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-related multimodal processing (audio with text and/or video), audio deep learning, or a related topic. The post holder would have experience in developing new research algorithms or methods, using languages
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type (iv) work with the computational biology team to transfer this information into a AI algorithm that can distinguish neurodegenerative and neuroprotective phenotypes (v) work with colleagues in
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dynamics, solid mechanics, soft matter or active matter. • To become familiar with simulation algorithms as needed, assist in the development of new ones, test and document any newly developed