71 distributed-algorithm-"Fraunhofer-Gesellschaft" Fellowship positions in United Kingdom
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to) fundamental research in machine learning or statistics, algorithm design, the application of AI methods in science, healthcare, social sciences, or business. You should have a PhD or equivalent level of
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development of future proposals for funding, into AI for renewable energy. You will consider ways in which the integration of machine learning algorithms might support the wider integration of, and uptake
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electrical power distribution system. Prior knowledge on power system condition monitoring would be an advantage. Experience in project work would an advantage. Share this job Facebook Twitter LinkedIn Apply
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Experience with machine learning algorithms and ideally experience developing novel methods Understanding of basic biological principles and experience interpreting ‘omics data Ability to analyse information
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infrastructure. We welcome applications from passionate, skilled, and committed individuals. About the Role The spatial distribution of schistosomiasis coincides with development of certain water management
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affordability, welfare, and income distribution. Contribute to the preparation of policy briefings, academic publications, and public-facing reports. Present findings in academic and policy settings, including
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(SDR) platforms and characterise them in the presence of interference in a variety of spectrum sharing scenarios, seeking opportunities for algorithms which provide enhanced interference resilience
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10 minutes and machine learning algorithms to deliver quantitative diagnosis without destroying the samples. The AF-Raman prototype will be integrated and tested in the operating theatre
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of schistosomiasis across rural-to-urban settings and develop tools to support targeted interventions. A key focus will be on mapping snail vector distribution near expanding water infrastructure (e.g., sand dams) in
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that influence global ocean mixing, heat and nutrient distribution, and climate dynamics. Despite their importance, these currents remain poorly understood due to their intermediate scale and intermittent nature