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data sources (e.g., registry data, surveys, and organisations). Your competencies Digital methods such as machine learning based classification, computational text analysis, network analysis, web
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applications, spreadsheets, and data management tools. Ability to work independently while contributing effectively to a multidisciplinary research team. Preferred Qualifications Experience coordinating
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catalysts used in chemical processes. The successful candidate will combine state-of-the-art quantum chemical modelling alongside machine learning techniques and contribute to the development of predictive
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to quality, integrity, creativity and cooperation. You have a profound knowledge of wireless communications, networking, and signal processing. You have at least intermediate knowledge of machine learning
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collaboration with a leading architectural firm. The candidate is expected to publish in leading Human-Computer Interaction venues. Your competencies You hold a master’s degree in human-computer interaction
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research experience in the mathematics of machine learning. Review of applications will begin immediately and continue until the position is filled. BACKGROUND CHECKS/CLEARANCES Employment with
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Developing computational models and running computer simulations in science and engineering still requires substantial expert knowledge. Agentic artificial intelligence (AI) offers a great
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strain-rate/high temperature interface contact layer created during LFW of Titanium alloys and the links to key process variables and machine/tooling behaviour. This study will be undertaken using
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-Machine Interfaces (eHMIs) can enable safer and more inclusive interactions. You will: Develop a theoretical framework for identifying key characteristics of AV–VRU interactions and define design criteria
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optimisation tools for aperiodic lattice metamaterials. The research will integrate physics-based modelling with machine learning to enable the efficient exploration of vast design spaces defined by