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and accepted to the PhD program at Stockholm University. Project description Project title: “Deep learning modeling of spatial biology data for expression profile-based drug repurposing”. A new exciting
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of methane dynamics in rapidly changing ecosystems and contribute to improving predictive models of future methane emissions. Field sampling will focus on regions where methane cycling is still poorly
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discover therapeutic targets relevant to Welsh populations. You’ll also help translate your computational insights into lab-based validation using experimental models, paving the way for new diagnostics and
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systems using various tools and models, including: i) characterization of the emerging patterns in physical systems (solid state materials and active systems); ii) investigation of the mechanical properties
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, including patch-clamp electrophysiology, high-resolution imaging, chemogenetic manipulation of glial activity, and behavioral assays in rodent models Analyze and interpret complex datasets from
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| £20780 + £2500 industry top up (per annum (tax free)) Overview This exciting, fully-funded PhD opportunity invites applications from candidates with a robust foundation in data science, modelling, and
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understanding of district heating and cooling, renewable energy integration, multi-energy systems, and energy conversion and storage technologies. You have strong skills in programming, modelling, and data
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according to TV-L • Flexible for families: flexible working time models, the option of a place in the company day-care center and offers for those returning from parental leave • Provision for later
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invites applications from candidates with a robust foundation in data science, modelling, and/or engineering, and a keen interest in deploying data analysis and artificial intelligence (AI) to solve real
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to mechanical forces. We work with leading international groups on modeling and also conduct simulations at DTU. Our overarching goal is to understand and predict the mechanical behavior of metals during plastic