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85748, Germany [map ] Subject Area: Physics / HEP-Phenomenology (hep-ph) Appl Deadline: none (posted 2024/08/04) Position Description: Apply Position Description Applications are invited for several Ph
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Assoc Prof Liton Kamruzzaman, Prof Hai Vu, Prof Graham Currie, Prof Eric Miller (University of Toronto), and Prof Roger Vickerman (University of Kent). Together, the team aims to: Define sustainable size
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period. Enquiries regarding the application process may be directed to Prof. Serena Best at smb51@cam.ac.uk or Prof.Ruth Cameron at rec11@cam.ac.uk Please quote reference LJ46434 on your application and
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scales and different phases which leads to nonlinear time and history dependent material behavior. Additionally, innovative changes are happening in the steel production process, especially in the drive
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Your Job: You will work in the Electrocatalytic Interface Engineering department, which is headed by Prof. Dr.-Ing. Simon Thiele. The department focuses on the fabrication, analysis and simulation
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Support Grant of up to £5,000 Access to Disabled Student Allowance, paid sick leave and paid parental leave Supervisor: University of Warwick: Dr Arnab Palit, Prof Andy Metcalfe Eligibility: Satisfy UKRI's
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subsequent precipitation hardening process. In addition, promoting a circular economy in the aluminium industry by increasing recyclability and using more recycled aluminium is essential for saving resources
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publish it as your PhD thesis. Your team Your WUR supervisors will be Dr. Paul Smeets and Prof. Dr. Ciarán Forde (Sensory Science and Eating Behaviour chair group). Dr. Davide Risso, external research
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 2 months ago
Job Code: 17-25 Job Offer from June 04, 2025 The Department of Prof. Dr. Stefan W. Hell invites applications for a PhD position at the intersection of optics, molecules and biophysics
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operational employment. This doctoral research will thus leverage the power of graph neural networks – a novel ML architecture, capable of learning fundamental physical behaviour by modelling systems as graphs