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to achieve, at least a 2.1 honours degree or a master’s in a relevant science or engineering related discipline. Applicants should have strong background in Machine Learning and Deep Learning. To apply, please
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one of the following analysis techniques (multiple preferred): normative modelling, dimensionality reduction techniques, machine learning, deep-learning, state space modelling, advanced statistics
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centres, we provide an unparalleled learning environment for its 24,000 students and 13,000 staff. At Cambridge, our mission is to contribute to society through world-class education, learning, and research
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an excellent publication (or papers in press or equivalent) track record in high quality peer reviewed journals. Evidence will be sought of a deep understanding of the applicant's previous fields of research and
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, motivation to learn new skills as well as excellent written and oral skills is essential.Example publications from the Lab:•Detection of host cell microprotein impurities in antibody drug products. 2024 Nature
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techniques, would be an advantage. The ideal candidate will have a deep interest in the algorithms that power graphics and a creative mindset, eager to think outside the box and develop novel solutions
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the accurate prediction of reaction enthalpies and activation free energies for all relevant intermediates. In this project, a deep learning and generative design toolchain will be developed resulting in an ML
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memorisation capabilities of deep learning models. Such vulnerabilities expose FL systems to various privacy attacks, making the study of privacy in distributed settings increasingly complex and vital
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existing experience. This position is part of the CDT in Net Zero Aviation, which offers a modular, cohort-based training programme with emphasis on innovation and impact, collaborative working and learning
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the CDT in Net Zero Aviation, which offers a modular, cohort-based training programme with emphasis on innovation and impact, collaborative working and learning, continuous development, active engagement