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data. Apply knowledge in a way which develops new intellectual understanding. Contribute to developing new models, techniques and methods as required by their research project. Present research outputs
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, www.iemr.no. via Unsplash Requirements We ask all applicants to respond to the qualification requirements. Applications lacking this information will not be considered. Applicants must hold a PhD in life
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position, funded by ALRI, offers an initial one-year appointment, with renewal contingent upon availability of funding. Conducts cutting-edge research in artificial intelligence, machine learning, and data
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Job no:520746 Work type:Full Time Location:Crawley Categories:Engineering and Mathematical Sciences, Social Sciences Lead numerical modelling of carbonate sand for offshore foundations, support
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sections, incorporating uncertainty quantification into AI/ML models and providing useful information in aid of UQ in AI/ML models to discern patterns in physical properties. The position will be highly
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methods for monopiles and validating models through centrifuge testing. Contribute to research dissemination through publications, conferences, and supervision of students. About you PhD or equivalent
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leveraged to accelerate learning from both classical and quantum data. The project will develop rigorous theoretical frameworks to understand key properties of quantum machine learning models—expressivity
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Social and Historical Sciences. For more information, please visit http://www.ucl.ac.uk/about UCL Mechanical Engineering has been pioneering the development of engineering education, having taught the core
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for publication, research seminars etc Supervise students on research related work and provide guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and
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. This is a grant funded position. Key Responsibilities Designing and executing cutting-edge experiments using cell lines, ex vivo cultures, and genetic mouse models. Lead collaborative projects, contributing