480 phd-in-computational-mechanics-"Prof"-"Prof" Postdoctoral positions in United Kingdom
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Vision, Robotics, Evolutionary Computation, Deep Reinforcement Learning, and Machine Learning. This should include a proven publication track record. You should also have: Research Associate: A PhD (or
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Biomedical Campus. You will join an exciting research programme investigating fundamental mechanisms of ribosome assembly, translational control and how defects in these processes drive cancer development
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evaluations, attacks on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related
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qualification/experience equivalent to PhD level in a relevant subject area (physics, engineering, computing science, etc.). You will need as essential skills a good knowledge of C and python, familiarity with
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qualification/experience equivalent to PhD level in a relevant subject area (physics, engineering, computing science, etc.). You will need as essential skills a good knowledge of C++ and python, familiarity with
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Associate: A PhD (or equivalent) in an area pertinent to the subject area, i.e. Computer Science, Machine Learning, Robotics. Research Assistant: A Master’s degree (or equivalent) in an area pertinent
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research experience in mechanics of flexible structures. The post, under the supervision of Dr Draga Pihler-Puzovic, must commence before 1st October 2025 and will focus on designing novel mechanical
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About the Role You will develop and apply novel computational methods to quantify the societal impact of fundamental science discoveries. Candidates close to completion of their PhD will initially
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the risks. You will have: a PhD in one of the relevant STEM disciplines, such as mathematics, statistics, computer sciences, theoretical food, ecological or physical sciences, etc. skills in mathematical
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models