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field. Strong computational chemistry background in atomistic simulations, electronic-structure theory, DFT, structure-property relationships, and interpretation of simulation results. Hands-on experience
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IRCM - Cancer Research Institute of Montpellier | Montpellier, Languedoc Roussillon | France | 3 months ago
, Computer Vision, AI, Medical Imaging, or a related discipline. ● At least 3 years of research experience (post-PhD), ideally in an academic or public research setting. ● Solid grasp of deep learning theory
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behaviour change theory (e.g. COM-B, the Theory of Planned Behaviour, or the Value-Belief-Norm model) as applied to sustainability or circular economy contexts. Experience with citizen science, co-creation
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in the Materials Theory, Informatics, and Design Group, led by Professor Liping Yu in the Department of Materials Science and Engineering at the University of Central Florida. The successful candidate
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encouraged to integrate into the Theory, Data, and Computation Group and support an equitable scholarly environment in research, mentoring, and service. Your work will focus on multi-physics simulations
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meetings, and support open research through well-documented code and data. The position is particularly suited to a researcher with strong mathematical intuition, experience of structured or non-paraxial
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, reaction-microscope instrumentation and spin-sensitive detectors Dedicated support from electronic and mechanical engineers and close collaboration with leading international theory and experimental groups
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. We also live by our Purpose and Values and our Staff Code of Conduct. At Durham we actively work towards providing an environment where our staff and students can study, work and live in a community
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codes and process their results. Helping to develop new models and algorithms to simulate pulse propagation, the material response, and other aspects of our experiments. Coding in Julia and python. Take a
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through data-driven modeling and optimization. The successful candidate will work at the intersection of thermal-fluid sciences, control theory, and artificial intelligence/machine learning to advance