467 assistant-professor-computer-"https:"-"https:"-"https:"-"https:" PhD positions in United Kingdom
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Research Assistant (“pre-doc”) to work closely with Dr. Stephen Jarvis on a research project at the intersection of environmental economics and energy markets. The successful candidate will play an integral
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of tomorrow and creating novel solutions to major global challenges. Our community is made up of 120 nationalities, 14 000 students, 400 professors and close to 5000 faculty and staff working on our dynamic
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, this research seeks to produce AI-ready data creation techniques that will help establish scalable, globally relevant AI solutions and elevate paediatric healthcare to the standards seen in adult medicine
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Location: West Cambridge A position exists, for a Research Assistant/Associate in the Department of Engineering, to work on compressor aerodynamics. You would develop key technologies and designs
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awareness These funded PhD scholarships are suitable for students with a background in Computer Science, Mathematics, Engineering and Cognitive Science. Students with interests in machine learning, deep
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Exciting Fully Funded PhD Opportunity: Novel Sealing for High-Pressure H2 and Low-Carbon Storage Technologies - Help Shape the Future of Clean Energy Storage! School of Mechanical, Aerospace and
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Institutes: https://www.ncl.ac.uk/engineering/ Key Accountabilities Research Assistant Collect, analyse and interpret research data and draw conclusions on the outcomes Co-ordinate own work with that of others
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challenges. Produce technical reports, presentations, and publications. Engage fully in the KTP Associate training and professional-development programme. What we are looking for: Research Assistant: A first
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PhD studentship in Computer Science: From Formal Requirements to Specification-based Automated Testing for Safety-Critical Medical Device Software Certification Award Summary 100% fees covered, and
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integrating machine learning, computational modelling, and experimental validation. The successful candidate will receive training in both computational and experimental biology within a highly collaborative