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of the quantum machine learning task. You should have a strong background in theoretical physics, quantum computing, or machine learning and have completed or be in the final stages of a PhD in this or a related
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simulations, machine learning and data analysis, and the opportunity to collaborate with experiments. This position would suit a researcher who has recently completed a PhD in Chemistry, Biochemistry
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Knowledge of machine learning or multi-omics data integration would be highly desirable Essential Application/Interview Deep interest in musculoskeletal research and translational science Essential
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SMDR. About you To be successful in this role you will be able to demonstrate the following: A PhD in a relevant subject area. Extensive lab experience, preferably with catalytic reaction systems. Prior
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swarm learning experiments, and provide technical input to establish local machine learning capabilities. The post offers opportunities to work closely with academic and industry partners, both within and
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population genetics, bioinformatics, computational biology, statistics or probabilistic machine learning and computer science. Experience of working with large genotyping or sequencing data sets A proven
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& National Security), underpinned by cross-cutting Fundamental Research. In the Environment & Sustainability Grand Challenge, we will develop machine learning and AI as a transformative technology to benefit
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Applications are invited for a PhD project within the Faculty of Engineering, in the Centre for Additive Manufacturing research group (CfAM) at the University of Nottingham. The student will work in
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also have or be close to completing a PhD in any of the following areas as well as the will and commitment to learn relevant topics from the other areas: Statistical and machine learning, mathematical
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brings together expertise in health data science, microbial genomics, and cancer bioinformatics. Th selected student will work under the supervision of Dr Arron Lacey, a specialist in machine learning and