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Field
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, artificial intelligence/machine learning, digital twins, and blockchain technology for operations and maintenance. This position is part of the Maritime Future Fuels Training Plan project, which aims
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) project (led by the Immigration and Naturalisation Service of the Netherlands Ministry of Asylum and Migration and co-funded by the European Union), awarded to Project Lead Dr George Brown of Lancaster
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engineering, or related disciplines who are passionate about applying machine learning to real-world clinical challenges. The successful candidate will lead the development and validation of predictive models
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execution. This work involves creating frameworks for adaptive decision-making, using techniques from operations research and machine learning. This particular thematic area will be supervised by Associate
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difficulties in the research projects. It is essential that you hold a PhD/DPhil in a quantitative discipline (eg Operations Research, Management Science, Statistics, Machine Learning, Applied Mathematics
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• Previous publications related to single cell sequencing analysis and mouse genetics • Previous experience in programming in Python, and/or application of machine learning for analysing data
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to conduct multidisciplinary research around robot learning for autonomous robotic chemists, with a background of excellent research outputs across Robotics and Machine Learning, ideally with a background in
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to conduct multidisciplinary research around robot learning for autonomous robotic chemists, with a background of excellent research outputs across Robotics and Machine Learning, ideally with a background in
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skills. Aware of the ethical issues around working with Big Data. Desirable criteria Experience applying advanced statistical or machine learning methods to complex datasets. Evidence of involvement in
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statistical or machine learning methods to complex datasets. Evidence of involvement in grant writing or development of independent research ideas. A commitment to teaching the next generation of researchers