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modelling, and machine learning approaches to analyse large-scale datasets, including bulk and single-cell sequencing, gene expression arrays, proteomics, and metabolomics. Working closely with senior
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, and excellent learning and development opportunities. Informal Queries For an informal conversation about this role, please contact Dr Awinder Kaur, Head of Digital Technologies and Machine Intelligence
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feedback using machine learning and control engineering methods. The project will be hosted at the Bristol Robotics Laboratory (BRL), the UK’s largest academic centre for robotics research, with access
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application of innovative Machine Learning (ML) frameworks to understand and predict the global hydrological cycle. The role will require bridging the gap between process-based physical modeling and scalable
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background in Computing Science/Cyber Security/Computer Networks/Software Engineering or combination of both with relevant IOT/AI, IT, programming skills (C++, Python, Java or C#, OS etc.), CISCO Networking
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remote and on campus working (Hybrid working ) For an informal discussion about the role, contact Amanda Harper, Director of Operations a.l.harper@bath.ac.uk We're very proud to be a signatory of the Armed Forces
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computational statistics, machine learning, theoretical statistics, and probability as well as applied statistics fields, including statistical and population genetics, bioinformatics, econometrics, statistical
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(Research Assistant) or PhD degree (Research Associate) in computer science or a related area or equivalent experience. Familiarity with standard machine learning libraries/data analysis, specifically as
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, computer vision, and predictive modelling, alongside excellent IT, analytical, interpersonal and communication skills in spoken and written English. You must be able to collect, process and present data with
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will hold a PhD (or close to completion) or possess equivalent research experience in a relevant computational field such as data science, artificial intelligence, machine learning, computer science