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independent researcher, including through grant writing, independent papers, consulting, trainings. The skills, qualifications and experience required to perform the role are: PhD in Machine Learning, Climate
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systems with electronic structure and/or machine learning methods, including (or be about to obtain) a PhD in a relevant area. Experience in high-level electronic structure theory such as coupled cluster
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relevant field such as NLP, Information Retrieval, Artificial Intelligence or Machine Learning and be able to demonstrate a strong track record of independent research and high-quality publications
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platforms will be designed, capable of efficiently exploring complex mixed variable design spaces on the microlitre scale. Our multisite reactor network will be driven by next generation machine learning
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Applications are invited for a Research Assistant or Research Associate to work on efficient machine-learning systems for earth observation. The post holder will be part of the Computer Architecture
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; experience in programming, data management and interpretation; comfortable developing data-driven and machine learning approaches from experimental data; ideally has experience in blast engineering, or damage
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neuroscience, computational cognitive science, physics, mathematics, computer science, machine learning, engineering or a related field. Preference will be given to candidates with: previous experience in
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funded Innovator Award that brings together multidisciplinary experts in neuroscience, machine learning, clinical practice, clinical informatics with healthcare innovation (and pharmaceutical industry
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analytical skills and substantial experience in machine learning at scale are required. Detailed information on the requirements for the role can be found in the further particulars. The position is for 1 year
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addition to conducting research into DSP, the Research Assistant/Associate would explore the potential for machine learning (ML) in the optical access network. The focus of the research into ML for PON would be on reduced