652 data-"https:" "https:" "https:" "https:" "https:" "https:" "Aix Marseille Université" Fellowship positions in United Kingdom
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irradiated materials. This work will be under the supervision of Prof. Enrique Jimenez-Melero, UKAEA Joint Chair in Materials for Fusion (https://www.birmingham.ac.uk/staff/profiles/metallurgy/jimenez-melero
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advised that normally your references will be contacted prior to the interview. For more details and/or to apply on-line please access: https://jobs.nottingham.edu.cn/job/184375/ If you are unable to apply
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Management approval, as appropriate and in conjunction with principal investigators. Manage data handling and interpretation of research results and take the lead in writing papers for publication in
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that are relevant to industry demands while working on research projects in SIT. The researcher will be part of the team of the MCCS NATURE Project (https://www.nparks.gov.sg/Cuge/Programmes-Schemes/Research
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, focusing on the development and application of data analytics methods to process multimodal data to provide clinically useful insights into bipolar disorders. This is part of the £3m 5-year Wellcome Trust
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testing while maintaining compliance. Curate, standardize and integrate historical and statistical data to form the foundation of a structured database for construction QA/QC and traceability. Design and
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THIS VACANCY IS OPEN TO INTERNAL APPLICANTS ONLY About Us We are offering an exceptional career opportunity for an accomplished Research Fellow to support the data analysis and data management team
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area with the potential to drive significant improvements in health and healthcare. You will be based within the Leeds Institute for Data Analytics and part of the Leeds Institute for Cardiovascular and
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applications. The role will focus on creating demonstrator platforms that combine sensing, data integration, analytics, and visualisation to support better understanding and management of energy use, flexibility
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analytical backbone of the programme. It develops sensor-enabled diagnostic cells, multi-modal data pipelines and hybrid physics-informed machine learning approaches to understand interfacial behaviour during