874 evolution-"https:"-"https:"-"https:"-"https:"-"https:"-"Ulster-University" PhD positions
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efficiency, consistency and patient outcomes; they also introduce new cognitive demands, risks, and accountability challenges. This project aims to contribute to the development of human-centred, safe, and
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that TEs fundamentally shape genome function and evolution by affecting gene expression, rewiring regulatory networks, and driving change in chromosome size and structure. In recent years, research
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highly successful career in the water sector or in an academic role. We will support your development into a dynamic, confident and highly competent researcher with wider transferable skills (communication
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. The research will explore the development of hardware security primitives, embedded trust protocols, side-channel attack mitigation techniques, and tamper detection mechanisms. Additionally, the project will
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the development and validation of diagnostic and prognostic algorithms. Electronic Prognostics Systems: Facilities equipped to assess the health and predict the remaining useful life of electronic components
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contribute to the development of sustainable and data-driven manufacturing systems and will be conducted in collaboration with industrial partners and international research networks. Duties of the position
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the development of scientific networks in an international environment of the Göttingen campus and beyond. GAUSS provides the organisational and regulatory umbrella for this programme. It was founded in 2005 by
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academic development , which is open to all doctoral candidates. The courses are designed to help students obtain the qualifications necessary for the successful completion of their dissertations and to
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design to train new generations of engineers. Your supervisor will be Associate Professor Andrei Lobov . Duties of the position Complete the doctoral education Contribute to research, development and
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crucial insights. In this project, you will contribute to the development of AI-driven methodologies for experimental fluid mechanics , focusing on: Designing multi-fidelity neural networks for adaptive