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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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strong analytical skills and desirably some computer modelling experience, and an ability to work in a multidisciplinary team and engage confidently with partners. You will have a track record of
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lab has used whole-brain tissue clearing, light-sheet imaging, and machine learning to map the spatial and temporal dynamics of serotonin axon development. This project aims to establish a high
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Strong analytical skills and experience in developing and implementing machine learning/AI solutions using relevant languages and frameworks Excellent communication skills and proven ability to collaborate
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the Graduate Business Partnership (GBP) scheme and offers full-time hours (36.5 hours per week) on a 12-month contract. You will be based in the workplace at the Research, Innovation, Learning and Development
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contribute to advancing simulation-based testing methods for ADS. You will contribute to cutting-edge research projects, including the EPSRC-funded SimpliFaiS: Simplification of Failure Scenarios for Machine
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optimisation is also essential. Evidence of participation in funded R&D projects in the UK or overseas in some of the areas of: Wireless communications, MIMO, RIS, optimisation, machine learning and game
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contribute to advancing simulation-based testing methods for ADS. You will contribute to cutting-edge research projects, including the EPSRC-funded SimpliFaiS: Simplification of Failure Scenarios for Machine
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(particularly under extreme conditions), and/or the use of machine learning for solid mechanics/stress analysis problems are encouraged to apply. The job description presented here is deliberately broad due
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. Responsibilities include working with digital signal processing, advanced filtering techniques, dynamic feature extraction, time-domain and frequency-domain analysis, signal fusion and machine learning to enhance