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- UNIVERSITY OF VIENNA
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master’s (or international equivalent) in a relevant science or engineering discipline. We are looking for a motivated candidate with genuine curiosity about the research area and the drive to take a project
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physics-informed neural networks (PINNs). However, these approaches are still in their early stages of development and have yet to demonstrate their effectiveness for complex real engineering problems
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opportunity to undertake industrially linked research in partnership with Rolls-Royce (RR) at the RR University Technology Centre (UTC) in Electrical Systems at the University of Manchester(UoM). The UTC
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University Technology Centre (UTC) in Electrical Systems at the University of Manchester. The UTC researches a wide range of underpinning electrical technologies for applications in future gas-turbine engines
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is 2:1 in Electrical and Electronics Engineering, Mechanical Engineering, Physics. Mode of study Full-time or part-time Start date 1 February 2027 Additional Funding Information This is a self-funded
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One of the current challenges in electric vehicle (EV) technology is the development of electromechanical braking (EMB) systems to replace conventional hydraulic brakes and to integrate them with
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sensing systems. Applicant Requirements: We welcome applications from candidates who hold, or expect to obtain, a First-Class Honours degree (or equivalent) in Electronic Engineering, Electrical Engineering
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that extend beyond current capabilities. Potential targets include queues, deques, priority structures, linked structures, and new DNA-native information architectures capable of operating in vitro or in living
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, and more consistent. Current AI systems struggle because they assume a single correct answer, when geological evidence often supports multiple plausible interpretations; so, training AI to copy one
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is suited to candidates with a PhD awarded or close to completion (or equivalent experience), in electrical machines, drives, control, real-time simulation, or a closely related engineering discipline