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data (e.g. DFT, MP2) and experimental data into AI-driven pipelines for structure–property learning and reactivity prediction. Applying AI models to real-world problems in virtual screening, ligand
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structures consisting of biomass-derived materials. We will adapt interdisciplinary approaches to investigate the digital fabrication of sustainable materials. The recovery and recycling of the materials
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Details Title Postdoctoral Fellow in Geometric Machine Learning School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Applied Math Position Description A
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: https://www.imfid.org) - a logic-based, scalable framework for representing structural specifications and domain knowledge across complex engineering and industrial systems. The lab maintains a wide
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You will be an active member of the Pharmaceutical Engineering Group to develop new, and support ongoing, research activities. This role involves supporting and advancing research activities through
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. You will be routed to this when you click on the 'Apply' button. PhD degree in a relevant subject, such as chemistry, materials science or engineering. If you are near submission or have recently
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Science, Chemical Processes, or a related engineering discipline. A strong background in electrochemical surface science. Proficiency in elemental and structural analysis using various techniques. Knowledge
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Position overview This fixed-term position will be based at the School of Art and Design, working in close collaboration with the School of Engineering, the Fenner School of Environment and Society, and the
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partnership between RMIT and the Defence Science and Technology Group (DSTG), through the Centre for Advanced Defence Structures and Materials Experimentation (CADSME). If you're passionate about experimental
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network with leading universities globally. The on-campus concept provides a structured approach focused on applied research in strategically important topics aligned with Schaeffler’s strategic roadmap