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Field
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and murine models and employ a wide range of techniques to interrogate systems ranging from intact fresh tissue to individual cells. The Postdoctoral Scholar will contribute to ongoing projects
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effects. You will contribute to the numerical modelling part of the project, which will benefit from novel element level and centrifuge testing experimental results. You will set up and validate numerical
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candidate will join Dr. Siddharth Saksena’s research group, which focuses on advancing hydrologic modeling, flood forecasting, and hydroinformatics through the integration of artificial intelligence, physics
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Learning Lab. The successful deployment of statistical models and AI solutions relies heavily on the quality of underlying model assumptions and the learning algorithms they employ. The design of loss
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preliminary data, it combines mechanistic and translational immunology with bespoke in vivo models to define and exploit therapeutically relevant subsets. The Research Fellow will lead studies on cytotoxic T
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to fit Ca profiles in olivine and calculate associated cooling rates, 2/ an analysis of uncertainty propagation for these models, and 3/ a global unified database of existing data that could be used
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optimiser that accelerates both workflow efficiency and materials discovery. Main Tasks and responsibilities: AI4LSQUANT aims to accelerate quantum modelling by learning fast, accurate surrogates
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photosynthesis to join the new pilot study of Generative Pretrained Transformer for genomic photosynthesis (GPTgp). The GPTgp project aims to develop a foundational holistic model of photosynthesis that will scale
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implementation and data handling; iv) contribute to the intercomparison with simulations and outputs of one model (CISM); v) collect, organize and quality check output data from the participating modelling groups
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-based research into a vertebrate animal model, allowing easier translation to potential human health effects. Essential Functions: Performs cell culture and receptor activation/binding experiments