191 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "The Institute for Data" positions at University of Nottingham
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About the role – In this post, you will join a collaborative BBSRC-funded project focused on using metabolomics and machine learning to predict lameness outcomes in dairy cows. A typical day may
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using multimodal approaches including advanced imaging, nano-mechanical characterisation and machine learning techniques Developing physics-informed reliability models using experimental datasets
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physics or computational data analysis (Python/R/MATLAB, machine learning, or bioinformatics) is highly desirable. Interested candidates should send a CV to michael.chappell@nottingham.ac.uk . Applications
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into the sample of interest. Recently we have been using AI and machine learning to predict the distortion present and significantly speed up this correction process. This PhD project will take the latest in AI
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, particularly MRI, medical physics or computational data analysis (Python/R/MATLAB, machine learning, or bioinformatics) is highly desirable. Interested candidates should send a CV to michael.chappell
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CFD, thermofluids and machine learning. Experience in Python (or another language), machine learning frameworks, or CFD tools such as OpenFOAM is beneficial but not required. Applicants should hold (or
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We are looking for a researcher, whose expertise lies in machine learning or uncertainty quantification, to work with Professor Richard Wilkinson on an EPSRC-funded project entitled “Scaling Cardiac
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This exciting opportunity is based within the Power Electronics and Machines Control Research Institute at Faculty of Engineering which conducts cutting edge research into power electronics
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well as extensive experience in data analytics/advanced statistics/machine learning is desirable. Research experience in flavour science and/or food chemistry is advantageous. As a people-orientated individual, you
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understanding and process optimisation. The work will primarily feature the integration of high data-density reaction techniques, laboratory automation & robotics and kinetic/machine learning modelling