12 algorithm-"Multiple"-"U"-"Simons-Foundation" Fellowship positions at University of Birmingham
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algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It investigates how the unique capabilities of quantum computing
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inversion techniques and signal processing. Strong programming skills, Proficiency in scientific computing (e.g. Python, MATLAB, or similar) for algorithm development and data handling. Experience with sensor
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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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and refine algorithms and models for large-scale language processing tasks, with a focus on healthcare data Contribute to developing new models, techniques and methods for clinical machine learning
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the prevalence and risk of modern slavery. There will be a focus on Bayesian nonparametric methods and practical development of MCMC algorithms that can be applied to data. Translating the project findings
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. The ability to work independently, manage multiple tasks, and communicate findings clearly is essential. About the Project: Novel GM interventions for mosquito control could represent a step change in
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partners. Main Duties Improve, develop, implement, and apply advanced computational tools and workflows to process, analyse, and interpret large-scale LCMS-based metabolomics datasets across multiple species
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of siRNA-peptide conjugates across multiple human, primate and mouse cell lines. We are therefore seeking a highly motivated and organised individual with proven expertise in human tissue processing and cell
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prototypes. Top-down 4D characterisation of enamel structural evolution using macro- using multiple techniques at macro-, micro- and nano- scale resolution in macro- and micro-fluidics setups to observe enamel
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-learningdisability/ ) a team of researchers showed that adults with Profound and Multiple Learning Disabilities (PMLD) and their family carers were disproportionately impacted by the COVID-19 pandemic. The post holder