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of methodologists, clinical academics, and PhD students at the University of Warwick with a strong track record in world-leading cardiac arrest research. You are required to have an upper-second class honours degree
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exposure, and thermal fluctuations. Key Objectives: - Develop and characterize low-carbon materials with multi-functional properties - Assess mechanical performance and long-term durability under simulated
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an open observatory to track flood risk and neighbourhood change, integrating official spatial datasets (government flood maps, deprivation indices), housing market data (prices, rents), and community
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for Religious Studies, Bochum, and with experts in other related research fields. You will lead the development of your own PhD research, aligning it with the research objectives and Work Packages (in particular
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objective of this PhD position is to advance research in statistical signal processing and machine learning for microphone array data, with a focus on sensing under uncertainty. The successful candidate will
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that facilitate sustainable soil remediation and waste management. Project description The main objective of this project is to create a sustainable and cost-effective solution for managing PFAS-contaminated soil
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, which will allow you to track your application through its various stages. WHAT APPLICATION MATERIALS ARE REQUIRED? We ask you to upload the following documents to the application portal: • CV • Statement
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application! We are now looking for a PhD student in Integrated Circuits and Systems, at the Department of Electrical Engineering (ISY). Your work assignments The objective of this position is to develop
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on mechanistic study of high cor
-through system. The objectives of this work are: i) to unveil the driving force of the micro-galvanic corrosion onset; ii) propose several approaches to reduce the micro-galvanic corrosion; iii
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
between process parameters and material properties will be developed and subsequently exposed to Bayesian optimization to find the optimal set of parameters that improve process performance and material