72 computational-physics-"https:"-"https:"-"https:"-"https:"-"Simons-Foundation" positions at Cranfield University
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confidence, safety, and reliable shared decision-making. To achieve this, the programme offers two closely connected research directions. The first area focuses on real-time multimodal human trust sensing
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management. The program will combine desk based and experimental activities that will ultimately establish the most sustainable approach to treatment, recovery and/or disposal of the brines. The successful
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progression up to £29,370 per annum We welcome applications from digital specialists to join our newly established Process Automation and Improvement Team – driving smarter, more efficient ways of working
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mechanical, control or aerospace engineering, physics, mathematics, or other relevant engineering/science degree. The ideal candidate would have experience with computational modelling and control of dynamical
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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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. The studentship is funded by the Leverhulme Trust through the Connected Waters Leverhulme Doctoral Programme. Urban blue networks, including rivers, canals and wetlands, are dynamic systems that shape how cities
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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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and local authorities to ensure the University’s physical environment supports its long-term ambitions, including delivery of its net zero carbon commitment by 2030. About You You will be a senior
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: • Experience with programming (Python, MATLAB), • background in aerospace, computer science, robotics, or electrical engineering graduates, • hands on skills in implementation of fusion
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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