27 computational-physics "https:" "https:" "https:" "https:" "Caltech" uni jobs at Cranfield University
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through a competitive process. Studentships will be for four years full-time and will start in autumn 2026. Studentship opportunities are available at Aberystwyth University, Brunel University, Cranfield
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progression up to £70,000 per annum Senior Power Platform Business Process Specialist We welcome applications from forward-thinking digital specialists to join our newly established Process Automation and
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progression up to £51,298 per annum Power Platform Business Process Specialist We welcome applications from forward-thinking digital specialists to join our newly established Process Automation and Improvement
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progression up to £70,000 per annum Senior Power Platform Business Process Specialist - Team Leader We welcome applications from forward-thinking digital specialists to lead our newly established Process
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Apply online now at https://jobs.cranfield.ac.uk or contact us for further details on (E): peoplerecruitment@cranfield.ac.uk . Please quote reference number 5245. Closing date for receipt of applications
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Deadline 1 Mar 2026 - 00:00 (Europe/London) Country United Kingdom Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Other EU programme Reference
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resources planning. Water company resources planning is a mature process incorporating climate change and environmental protection with robust options development and clear governance. Various initiatives
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, chemical engineering, mechanical engineering, physics, or related disciplines are encouraged to apply. Experience with thermodynamics, corrosion, computational modelling, or high-temperature materials is
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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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collaboration in time-critical tasks. By integrating foundation models like large language models (LLMs) with physically embodied agents (e.g., drones or vehicles), the research focuses on enabling adaptive