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graduate with a background in the mechanics of materials or a related discipline, and a strong track record in developing computational models. The successful candidate should also have a good publication
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About the Role This is an opportunity to work as part of the team and project “Development of Multi-Modal Foundational Models and AI Accelerators for Zero-shot Intelligent Surveillance System
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Technology Laboratory (DSTL), Electromagnetic Environment (EME) Hub. About You Applicants should have a PhD in modelling hypothetical scenarios, with and without data, for structured decision-making under
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found at www.sems.qmul.ac.uk . QMUL is also home to the cross-cutting Centre for Predictive in vitro Models, providing a vibrant community of researchers active in the in vitro models area
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of murine models of high-grade lymphoma with the aim of providing pre-clinical evidence to support the development of metabolic inhibitors as novel treatments for lymphoma, alone or in combination with
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to work on a project investigating mechanosensing in flies (Diptera). This post will focus on using detailed wing geometry models and free flight kinematic measurements in computational fluid and structural
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modelling/AI and/or computational neuroscience, with strong computational skills. The post holder will provide research support in the area of computational neuroscience/AI and animal cognition, develop
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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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project on Addressing socio-technical limitations of Large Language Models (LLMs), particularly for medical and social computing (https://adsolve.github.io/ ). The role involves developing methods
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, Spain and Norway. The project runs until early 2028 and investigates the potential role of performance-based arts in understanding how coastal communities learn about and respond to ecological crises