27 software-engineering-model-driven-engineering-phd-position Postdoctoral positions at University of London
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have a PhD and track record in either computer science with specialisation in relevant AI technologies for surrogate modelling, or in Earth or Environmental Science with a strong track record in
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Research Assistant or Postdoctoral Research Associate About the Role This is a research position for an EPSRC funded project entitled “Distributed Acoustic Sensor System for Modelling Active Travel
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algorithms is desirable. About the Department This post is within the School of Engineering and Materials Science, a large School with 108 academics, more than 250 PhD students and over 2500 undergraduate
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Vitro Models. The project aims to use organ-on-a-chip technology combined with bioengineering approaches to develop, validate and use a suite of vascularised human tendon-chip models. These high quality
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the spectrum of Mathematical Sciences. It is part of the Faculty of Science and Engineering, which comprises five schools and two institutes. This position is based in the Centre for Data Science, Statistics and
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sociomaterial practices that shape decision-making around medicine use in pregnancy. The research will be informed by theoretical perspectives such as Science and Technology Studies (STS), including concepts
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dynamic strain and flow fields during flight. Candidates should hold a PhD in a relevant biology or engineering discipline and be competent with numerical simulations. Desirable competencies would include
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About the Role You will develop and apply novel computational methods to quantify the societal impact of fundamental science discoveries. Candidates close to completion of their PhD will initially
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2025. We seek to recruit a Research Associate specialising in statistical modelling and machine learning to join our multi-university multi-disciplinary team developing a groundbreaking technique based
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About the Role This Postdoctoral Research Associate (PDRA) position is part of an exciting EPSRC-funded programme, "Enabling Net Zero and the AI Revolution with Ultra-Low Energy 2D Materials and