31 computational-physics "https:" "https:" "https:" "https:" "LaTIM Brest" PhD positions at Cranfield University
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covers fees and stipend for a home (UK) student with funding provided by the Leverhulme Trust through the Connected Waters Leverhulme Doctoral Programme. Options exist for PhD and Master + PhD routes
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Resilience (WIRe). The WIRe programme offers a bespoke training programme in technical and personal skills, access to world-leading experimental facilities. The successful candidate will also have the
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. The project focuses on power-aware computing, thermal optimization, and sustainable electronic design, targeting critical applications in aerospace, healthcare, and industrial automation. Hosted by the renowned
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, embedded intelligence, and adaptive cyber-physical systems that operate safely under uncertainty and dynamic conditions. This PhD at Cranfield University explores the development of resilient, AI-enabled
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, and flexible working arrangements ideal for computational and field-integrated PhD research. Methodology You will develop a process-based, spatially explicit population model for European amphibians
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fees. Diversity and Inclusion at Cranfield We are committed to fostering equity, diversity, and inclusion in our CDT program, and warmly encourage applications from students of all backgrounds, including
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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/physics/biology) or engineering. The ideal candidate should have some understanding in the areas of Materials Science, Chemistry, Physics, Metallurgy, or Mechanical Engineering. The candidate should be self
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of representative failure models for gear failures causes difficulties in their useful lifetime prediction. Critical operational parameters such as loading, speed and lubrication affect the physics of gear meshing
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. The integration of AI into hardware not only enhances performance but also reduces energy consumption, addressing the growing demand for sustainable and efficient computing solutions. This PhD project delves