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experimentation and thermodynamics calculations. Establish a high-throughput bulk materials processing route to enable efficient characterisation and parallel testing of multiple compositions. Develop a high
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skills and qualifications: A recent PhD (completed within the last 5 years) in computer science, electrical engineering, or a related field. Strong background in network interconnect design and
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. We are now looking for: Three (3) Doctoral Researchers (PhD students) in Machine-Learning-Driven Atomistic Simulations The Data-driven Atomistic Simulation (DAS) group, led by Prof. Miguel Caro
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on the platform CUDA for parallelization of the computation over several GPUs’ cores, and has interfaces with Matlab and Python for ease of use. However, powerful as it is, MagTense is at present limited in its
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/ ). This position will be fully funded until March 2028. For further information on Dr Edward Johns’ research and projects, see www.robot-learning.uk . You will be assisting PhD students and a post-doc in developing
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; contributing to (or leading) technical reports or manuscripts prepared for submission to peer-reviewed journals; and mentoring graduate students. Qualifications: PhD in mathematics or a closely related field
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and processes) by shadowing as well as receiving coaching and tutoring from one of our Senior PA Engineers. You will perform this task in parallel to specific Mission Classification activities described
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MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA | North Ryde, New South Wales | Australia | about 2 months ago
Initiate and maintain academic and industry collaborations, and apply for research funding Communicate research findings in scientific journals and at conferences About You You will have completed a PhD in
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apply for research funding Communicate research findings in scientific journals and at conferences About You You will have completed a PhD in genome engineering, synthetic biology, or a closely related
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-economic environment in Morocco and Africa. HTMR provides highly automated and parallel approaches to the development of new materials and processes. HTMR allows scientists from all UM6P research community