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Field
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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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. Qualifications • PhD Degree in a relevant discipline, e.g. electrical / electronic engineering, computer engineering, computer science, etc. • Full experience in computer graphics and robotics area
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-performance computing, machine learning models (eg. LLM), probabilistic models for data, novel techniques for making measurements, visualization tools, and community-oriented foundational software tools. Please
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. Candidates should either hold a PhD in Computer Science, Information Technology, or a closely related field OR hold a PhD in any field in combination with strong computer programming and data visualization
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basis including at the annual appraisal. As duties and responsibilities change, the job description may be amended in consultation with the post-holder. Qualifications PhD degree in Biomedical sciences
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to optimize training and inference processes Conduct experiments to compare with comprehensive baselines and validate results Job Requirements: Preferably PhD in Computer Engineering, Computer
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science, medical statistics or machine learning methods Advanced knowledge of electronic healthcare records and their use in development and validation of risk prediction models Knowledge in application
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health data, such as electronic health records or biobank-scale resources (e.g., UK Biobank, All-of-Us, FinnGen). Familiarity with machine learning approaches, such as penalised regression, deep learning
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have exceptional resources to facilitate research including access to administrative, research, and computer support staff. Required Qualifications* PhD degree or equivalent in epidemiology, gerontology
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neuroimaging and fluid biomarkers, (b) systems biology analysis of pathways from multi-omics data using multi-layered network approaches, © machine learning for identification of genetic risk factors in ADRD, (d