418 data-"https:"-"https:"-"https:"-"https:"-"UNIV" Fellowship positions in United Kingdom
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(one day per week) and is available as a fixed term contract until 01/02/2027, with the possibility for extension. Further information is available in the role profile. To apply for this vacancy please
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) and is available as a fixed term contract until 01/02/2027, with the possibility for extension. Further information is available in the role profile. To apply for this vacancy please click ‘Apply Now
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outputs with electrochemical performance data from a variety of analytical techniques (e.g. diffusion, conductivity, power density etc) (D) Highly confident and articulate with outstanding communication and
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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7 Jan 2026 Job Information Organisation/Company University of Nottingham Research Field Juridical sciences » Criminal law Juridical sciences » Public law Juridical sciences » Other Researcher
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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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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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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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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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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