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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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(UKHSA), and aims to investigate use of machine learning for prediction of infectious diseases outbreaks. Using data from routine surveillance of respiratory infections in the first instance, the
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be part of a small team, led by Dr Susanne Bornelöv, which studies gene regulation using various approaches including machine learning, evolutionary genomics, and sequencing bioinformatics. Our team is
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protein design and evolution, using molecular biology and biophysics along with the latest AI or machine learning tools. According to the development of the project there may be the chance to learn other
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grant funding remaining in place. Holding a PhD in Music or a related discipline and with a record of, or clear potential for, outstanding research, you will be a scholar whose research activities fall
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. The PDRA should have a relevant specialist area in data science, including managing and structuring data, programming, developing and applying theoretical methods and machine learning models for data
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PhD in a relevant subject area. Excellent knowledge of machine learning and experience of applying machine learning techniques is expected. Familiarity with efficient ML techniques, edge AI hardware
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data-driven big data and machine learning approaches. The Research Associate would be responsible for undertaking the study in Cambridge, as well as some aspects of study co-ordination or data analysis
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with biophysical models and machine learning methods, to studies in both mouse models and patients. Applications are invited for a Research Associate to join the VISIONLAB, which is co-located in the Department
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. with R and Python. Experience in machine learning. Background in molecular biology concepts and an interest in immunology. Passion for unravelling complex biological systems. Excellent communication and