203 structural-engineering-"https:"-"https:"-"https:"-"https:"-"Dip" Postdoctoral positions in United Kingdom
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, decision-maker education campaigns, and training the next generations of technology governance leaders. It is one of the few organisations in the world to focus on the governance of AI from both technical
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to work within one of, or across, the four research themes: Learning with Structured & Geometric Models, Low Effective-dimensional Learning Models, Implicit Regularization, and Reinforcement Learning
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testing for all three projects. Applicants should hold a relevant PhD/DPhil (or be close to completion) in engineering or a related discipline. Post-qualification research experience and a strong
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research project lead by Oxford Materials (Professors Robert House (PI), Saiful Islam, Peter Bruce), with UCL Chemical Engineering (Dr Rhod Jervis) and 4 industrial partners that brings together expertise in
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agenda for sustainable livestock in Europe. You will also help design and facilitate structured stakeholder/scientific workshops to review and refine these findings. You will be responsible for integrating
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effects while building machine-learning-ready kinetic datasets for predictive catalyst design. You should have a PhD (or about to obtain) in Chemistry or field related to this project (Chemical Engineering
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of researchers to develop new heterogeneous catalysts for conversion of CO2 to light olefins using high-throughput experimental techniques and AI tools. You will have a PhD in chemistry or chemical engineering, a
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Point 25 - 28 £33,482 - £36,130 until confirmation was received. This post is available from 30 March 2026 for an initial period of 12 months. Based within the Faculty of Science, Engineering and Business
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Experience in participating in research projects Didactic skills / experience in e-learning IT skills Knowledge of university processes and structures is desirable Excellent knowledge of English (C1) GFL
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and testing of LLMs. About you You will hold, or be close to completion of a PhD/DPhil in a relevant technical subject (e.g. computer science, statistics, engineering) and possess sufficient specialist