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applications (e.g. natural language processing, multivariate time-series data), to develop systems that improve the efficacy of machine learning-based technologies for healthcare applications. You must hold a
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reasoning processes to enhance transparency and accountability; (5) assess privacy risks of watermarking; and (6) conduct privacy preservation assessments, including training data extraction and membership
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, building the experimental apparatus, conducting the experiments, analysing the data, and producing the manuscripts for publication (as first author), as well as disseminating the results of the project
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vulnerabilities (including to security and privacy) that may be introduced when AI is used to process data from wearable devices such as ‘smart glasses’. The project involves academics from Universities
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of what criteria will be assessed at each stage of the recruitment process. Further information: We pride ourselves on being inclusive and welcoming. We embrace diversity and want everyone to feel
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research skills, provide instruction or plan/ deliver seminars relating to the research area. The successful candidates will have a PhD (or expect to soon be awarded) in the physical or biological sciences
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candidate will help to support the team to formally document algorithms within a quality management system. EpiNav™ provides state-of-the-art computer-assisted support for the planning of stereotactic
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into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data
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.) if candidate holds a relevant degree and is working on PhD/DPhil) together with established knowledge in wired computer networks and sustainable computing, significant coding experience (both Python and C/C
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computer codes to solve some of the daily research problems and have experience with high performance computing. You should have a PhD in Chemistry, Physics or Materials Science with a proven research track