226 structural-engineering-"https:"-"https:"-"https:"-"https:"-"UCL"-"UCL" Postdoctoral positions in United Kingdom
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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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, as well as implementation and further development of Oxford Nanopore technology (ONT) based long read sequencing workflows. Furthermore, implementation and customization of bioinformatics workflows
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year. The project focuses on experimental investigation of structural and dynamic properties of colloidal monolayers driven out-of-equilibrium. The successful candidate will join an ambitious research
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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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Specification Essential Criteria: Qualifications 1. An excellent first degree in area of specialism (e.g., cyber security, computer science, maths, or electrical engineering) 2. Normally, a PhD (or be close
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THE CENTER FOR MATERIALS INNOVATION AND TECHNOLOGY (CMIT) Materials science underpins nearly every modern technology from clean energy and AI to electronics, biomedicine, defense, and space
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scientific discoveries and technological innovation. As a hub for interdisciplinary research, our institute brings together world- class scientists, engineers, and scholars to address the most pressing
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status, parental status, race, religion or belief, sexual orientation, or trans status or history. More information on our structures and initiatives around EDI, including information on staff diversity
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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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Computer Science, Chemistry, Chemical Engineering, Physics, or Materials Science. You will develop optimisation and machine-learning algorithms for human- and literature-informed discovery of new materials