472 computational-physics-"https:"-"https:"-"https:"-"https:"-"Simons-Foundation" PhD positions in United Kingdom
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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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of the advertised projects, contact the relevant supervisory team. If it is more general, contact the programme or one of our Directors . You can also contact us at any stage later in the process. When you are ready
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autonomous systems. You will have the freedom to shape the project direction, experiment with novel ideas, access state-of-the-art AI and computing facilities, receive tailored training and professional
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and determination? We are currently seeking a/an University assistant predoctoral - PhD Position in Graph Learning 39 Faculty of Computer Science Startdate: 01.05.2026 | Working hours: 30 | Collective
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supervisor, Dr Ana Blanco, if you have any questions. Entry requirements: Applicants should have, or expect to achieve, a first-class/high 2:1 degree in a relevant engineering or physical science discipline
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supervisor - Dr Haitao Lan, if you have any questions. Entry requirements: Applicants should have, or expect to achieve, a first-class / high 2:1 degree in a relevant Engineering or Physical Science discipline
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integrating machine learning, computational modelling, and experimental validation. The successful candidate will receive training in both computational and experimental biology within a highly collaborative
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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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(with an average programme mark of no less than 65%) or international equivalent . Candidates should have a strong background in marketing, public management, sociology, or public health. Experience in
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, Chemistry, Physics, Engineering, Mathematics, Computer Science, Data Science, Machine Learning or Artificial Intelligence a minimum 2:1 undergraduate degree (or equivalent) Excellent spoken and written