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Field
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in nature and can be tailored to suit the interests and backgrounds of individual candidates. Applicants from diverse disciplines—such as construction, engineering, computer science, business and
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in radiation–matter interactions, computational modelling, and materials science, with a strong publication record (h-index 36, i10-index 69). Dr Francesco Fanicchia, Research Area Lead: Material
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PhD Studentship: Dissecting the Molecular Architecture and Function of LMTK3 as a Therapeutic Target
; University of Sussex | The City of Brighton and Hove, England | United Kingdom | about 2 months agomechanisms underpinning LMTK3's multifaceted role in cancer biology. By employing a multidisciplinary approach combining structural biology, biochemistry, and cell biology, this research aims to provide novel
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Fields: Open across ten schools covering disciplines such as Engineering, Construction, Computer Science, Law, Business, Arts and Creative Industries, Architecture, Health, and Education Duration: Standard
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
relevant field such as engineering, computer science, or applied mathematics. Experience or interest in AI, machine learning, or digital systems is beneficial. We welcome candidates from diverse backgrounds
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Can We Teach AI to Outsmart Humans in the Werewolf Game—Without Changing the AI Itself? Large Language Models (LLMs) have dazzled us with their ability to converse, code, and create—but they still struggle in areas where humans excel: reasoning about other players, forming alliances, and making...
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Fully Funded PhD Research Studentship tax-free stipend of £20,870 Design, Informatics and Business Fully Funded PhD Research Studentship Project Title: Behaviour-Based Anomaly Detection
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-based solutions (NbS) for water and wastewater treatment. The research will explore sustainable engineering strategies to boost their performance to deliver benefits for the environment and society. The
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fees will be covered for up to three years. Eligibility Applicants must have an undergraduate or postgraduate qualification in computer science, machine learning, AI or another relevant field. Equivalent
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Lead Supervisor name: Andrew Callaway, email: acallaway@bournemouth.ac.uk Project description: This PhD programme will determine the most clinically acceptable methods for emergency response teams