10 phd-scholarship-in-computational-material-science PhD positions at Chalmers University of Technology
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with expertise in materials characterisation, computer vision, computational modelling, and machine learning. The other PhD positions connected to the project are: PhD Student Position in Generative
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Are you interested in developing computational tools to understand the detailed mechanical behaviour of multi-phase materials? Then this PhD position at Chalmers University of Technology might be
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machine learning, computer vision, and materials science. The focus of this position is on development of neuro-symbolic models for the effective behaviour of the complex microstructure of recycled
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This PhD position is part of the WASP-WISE NEST project RAM³ – a multidisciplinary research effort at the intersection of machine learning and materials science. The project brings together PhD
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, Sweden. The student will form a part of a new NEST initiative funded by the Wallenberg Initiative Materials Science for Sustainability (WISE) and the Wallenberg AI, Autonomous Systems and Software Program
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crafting, material recycling and reuse, sustainable bio-design, and robotic manufacturing. The PhD student will be guided by leading researchers in architectural computational design and robotic fabrication
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partners in the project. Reporting results to industry and academic forums, as well as open science platforms. Contract terms The PhD position is fully funded from the start and has a scoped duration of 4
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establish an adaptive multiscale platform where catalyst performance is computed from first principles. Contract terms and what we offer The PhD-positions are fully funded from start As a PhD student at
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in the management of technology, people, and organization, and a desire to make groundbreaking contributions to the field of maintenance engineering. PhD Project overview The project focuses
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. The applicant should have strong background in mathematical foundations of computer science and experience in Python programming. Previous experience in deep learning, reinforcement learning, or explainable AI is