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data engineering, statistical modelling and natural language processing, including from partners at the South London and Maudsley NHS Foundation Trust and King’s College London. You will be supported
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discipline Relevant background includes any of: evolutionary genetics, phylogeography, landscape genetics/genomics, computational biology, statistics, applied mathematics, population modeling, evolutionary
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services, including research examining patient outcomes, referral pathways, and service delivery models. collaborate with researchers, clinicians, and stakeholders across a broad portfolio of projects
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Fellow will work primarily on an NSF-funded project related to studying how well AI models understand human emotions. The scope includes questions like: how do machines reason about human emotions in
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; Skills in computer programming. Workplan and objectives to be achieved: Development of Machine Learning tools for retrobiosynthesis pipelines, including: (i) validation and extension of models and tools
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, including model specification, robustness checks, interpretation of findings, and translation of results for both academic and policy audiences Overseeing fieldwork strategy and data quality, including
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mechanisms underlying spinal cord injury and recovery. Operating within a highly collaborative and well-equipped environment, you will utilise advanced mouse models to solve complex biological questions
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institutions provides long-term funded research-focused positions for early to mid-career researchers to pursue ambitious research programs. This position is modelled on the ethos and support offered by EMBL
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direct air capture solutions by assessing and designing reclamation processes for liquid absorbents used in CO2 capture. You’ll work across modelling, experimentation and pilot-scale activities
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treated. HARPNET’s scientific programme is integrated across three scientific work packages, where data, technologies and biological models will be shared across projects through joint supervision, network