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About the role - Applications are invited for the position of Technical Specialist for Simulated Learning. There are two positions available. The University of Nottingham is launching a new Medicine
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for the computer simulation of electronically excited processes in molecules and materials. In the age of net-zero it is more important than ever to obtain a deep, molecular-level understanding of the working
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Research Council rate (set at (£21,805 p.a. for 2026/2027 academic year) for 3 years. Please note the eligibility criteria set out by the UKRI at: https://www.ukri.org/what-we-do/developing-people-and-skills
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identification framework. The role involves developing a species-agnostic computational pipeline that integrates cutting-edge deep learning methods - such as AlphaFold2 and FoldSeek -to enhance protein function
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to the 30th September 2026. We are looking for outstanding machine learning researcher to join the Torr Vision Group and work on AI Scientists: systems that use foundation models, AI agents, and robotics
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engineering, machine learning, molecular design, and sustainability, helping to create smarter ways of identifying promising sorbents for electrochemical CO2 capture. Over the course of the project
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* together with relevant experience. You will have a strong technical background in machine learning, especially RL and LLMs. An ability to work independently and as part of a collaborative research team is
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will strive to continually excel as an innovative world-class university that makes a positive impact on society, living up to the University’s motto: “To learn and to apply, for the benefit of mankind
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Adversarial machine learning - Identification and prevention of cyber-physical attacks on infrastructure (S3.5-MAC-Champneys) School of Mechanical, Aerospace and Civil Engineering PhD Research
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collaboration with Special Melted Products (https://specialmeltedproducts.com/) using the unique Royce metals processing capabilities in Sheffield (https://sheffield.ac.uk/royce-institute), that range from alloy