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Electronic Engineering, Control Engineering, Computer Science or a very closely related topic: Strong understanding of power electronics principles Excellent knowledge on data-driven machine learning algorithm
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with verifiable experience in longitudinal data analyses methods, structural equation modelling, network analysis, machine learning and/or adaptive trial design. Essential are outstanding academic
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of the Armed Forces Covenant and welcome applications from service people. Further information For further information please contact Susannah Crockford, e-mail s.crockford@exeter.ac.uk . The closing date
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to revolutionize agriculture in Morocco by combining cutting-edge technologies, including crop growth models, remote sensing data, data assimilation, machine learning, and seasonal weather forecasts. As a
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and sensor systems for remote maintenance and reliable fusion operations. Artificial Intelligence Developing advanced artificial intelligence/machine learning (AI/ML) solutions for fusion science and
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: Research activities will be conducted in BSL-2+ laboratories. Learning Objectives: Under the guidance of a mentor, the participant will gain experience in: Animal studies: mouse and large animal inoculation
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of incorporating sensors, spectroscopy, imaging, and machine learning techniques into the postharvest processing workflows and/or pre-harvest evaluation of food quality and safety. The participant will have the
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, integrating the outcomes to inform future projected trend analysis. Applying statistical and machine learning to project future data analysis. Managing and analysing large data sets using efficient data
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or equivalent professional experience in a relevant discipline such as digital product development, human-computer interaction, UX-design, computer sciences. You will have knowledge of quantitative and
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Postdoctoral Fellow - Materials Chemistry, Texas Materials Institute, Cockrell School of Engineering
or parallel reactors Collaborate with computational scientists to integrate machine-learning models for closed-loop materials discovery Collaborate with companion postdocs on functional materials