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Field
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to apply advanced AI models in areas such as catalyst design, multi-scale modeling, and spectroscopic analysis. The Research Fellow will take on a significant role in machine learning theoretical energy
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power electronics Machine learning Renewable energy systems Advanced statistics Language requirement: Good oral and written communication skills in English English requirements for applicants from outside
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active role in developing novel machine learning based systems and tools on the path towards clinical use and implementation of AI for the treatment and care of individuals also from minority populations
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Are you an ambitious scientist looking for your next challenge? Do you have a PhD (or near to completion) in a quantitative subject, an interest in Polar research and the skills to develop our Earth
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of remote sensing data using physical, statistical and/or machine learning approaches Knowledge of the latest remote sensing techniques, key satellite missions (e.g. Copernicus) and their application
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machine learning is essential; while structure prediction or materials chemistry experience would be advantageous, it is not a pre-requisite for the role. This post would be ideal for an ambitious and
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machine learning is essential; while structure prediction or materials chemistry experience would be advantageous, it is not a pre-requisite for the role. This post would be ideal for an ambitious and
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in statistics, machine learning, mathematical modelling, or a related field, to join our research team in the Department of Applied Health Sciences. The successful candidate will work on an NIHR funded
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research is open; we are particularly interested in those working in the period between 1900 and the present. Open to scholars with PhDs in Science and Technology Studies and related fields whose research
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Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related disciplines. Knowledge of autonomous vehicles or cyber security will be