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Field
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interest in social science applications, and with strong competence in statistics and machine learning. The successful candidate will develop predictive models using machine learning and work alongside other
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of hydrological connectivity of soil moisture using gridded soil moisture data sets and data-driven approaches (e.g., complex network methods) Develop models to predict gatekeeper locations and their relationship
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neuroimaging data constrained by patient's structural connectivity and tractography • Using the results of the TVB model fits to stratify patients and predict disease progression • Organizing and unifying
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contribute to a major research project to improve our understanding of macroplastic pollution in coastal seas. Working at the intersection of numerical modelling and observations, you will develop simulations
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: Transform high resolution climate prediction. Job description Challenge, Change, Impact Warm tropical waters fuel intense storms, yet the fine scale exchanges of heat, momentum and freshwater between air and
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development of new computational and mathematical models to quantify and predict infectious disease risk, particularly for identifying high risk individuals and groups. The PDRA will translate conceptual
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Kogias as part of his ERC Starting project titled CloudNG (https://cordis.europa.eu/project/id/101220079 ). The post will be based in the Department of Computing at Imperial College London at the South
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controllability • Learning and calibration strategies for uncertainty-aware language model prediction • Knowledge-augmented and neuro-symbolic approaches for language-based reasoning • Evaluation and design of LLM
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, or engineering. Our research integrates mathematical modeling, machine learning, and quantitative experiments to understand and control the dynamics of microbial communities in time and space. Ongoing projects
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product models and conditions.While main innovations are expected in control and simulation, empirical validation and demonstration are considered equally important to ensure industrial adoption. Therefore