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well as physically-based hydrological model development. The principal supervisor will be Ylva Sjöberg at Umeå University, and the research involves an interdisciplinary team of collaborators at Gothenburg University
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equations. Your main research assignments will be to develop new models and methods for generative sampling and Bayesian inference. You will be jointly supervised by Assistant Prof. Zheng Zhao (https
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application! We are looking for a PhD student for sustainable and resource-efficient machine learning. Your work assignments Machine learning has recently advanced through scaling model sizes, training budgets
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environmental triggers, such as common viral infections and microbial exposures. With a strong translational focus, the group integrates cutting-edge molecular, cellular, and model systems to bridge fundamental
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scaling model sizes, training budgets, and datasets; often at substantial computational and environmental costs. This PhD project targets sustainable and resource-efficient machine learning with a focus on
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model for large scale assessments and projections of the land-water carbon cycle to variation in climate conditions. The detailed direction of the PhD studies will be discussed and decided jointly with
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cytometry, genome editing, and functional tumor models to decipher and engineer cytotoxic lymphocyte responses in cancer. We collaborate closely with clinical units at Karolinska University Hospital and
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and CH4) from headwaters, and use of machine learning and process-based model for large scale assessments and projections of the land-water carbon cycle to variation in climate conditions. The detailed
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from vascular lesions and blood, combined with genetic, clinical/epidemiological and imaging parameters from patients. We also perform in depth functional studies in animal and cell culture models
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transformations. The project investigates a hybrid approach that combines deep learning with grammatical inference to develop models that are interpretable, efficient, and mathematically verifiable while leveraging