9 condition-monitoring-machine-learning Fellowship positions at The University of Southampton
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modelling, satellite data assimilation, multivariate statistics, and machine learning. Prior experience with model and satellite products for mapping and understanding SM-dependent hazards (like floods
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or more of: the use of micro/nanofabrication and materials characterization tools; computational multi-physics/electromagnetics modelling and/or the application of machine learning algorithms; experimental
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: Genomics, precision medicine, bioengineering, and health data science AI and Digital: Machine learning, robotics, digital health, and cybersecurity Defence and Advanced Manufacturing: Secure systems
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under real-world conditions to verify system operation against targets and demonstrate the reliability of the technology for use in backup power, grid stabilisation, and renewable energy integration
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in distributed database systems, information retrieval, computer networking or semantic web. The post does not involve working outside of the UK for over 30 days in a row or over 90 days in a year. For
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responsible for maintaining high quality research procedures and will work as part of the team and liaise with three recruiting sites in setting up the study, monitoring participant recruitment, data collection
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We are looking for an excellent communicator and researcher in the area of chronic pain, with substantial experience working with people from minority communities and those with health conditions
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disabled people. As a Disability Confident employer with bronze Athena SWAN recognition (University Silver Award status), we demonstrate sustained commitment to creating equitable opportunities across all
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facilities and a range of discounts. Learn more about ECS at: https://talentedu.com/ecs/ We strongly encourage interested candidates to contact Dr. Shelly Vishwakarma (s.vishwakarma@soton.ac.uk ) to discuss