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on tungsten samples and candidate tungsten alloys will validate the simulations and guide the design of more dust-resistant materials. Finally, we will use machine learning to integrate simulation and
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economic modeling, with interests including improved spatial resolution and machine-learning-enabled approaches for policy analysis. Postdoctoral Position (f/m/d) – Integrated Assessment Modeling (Climate
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biomedical engineering, electrical engineering, machine learning, statistics, computer science, or a related area considered relevant for the research topic, or completed courses with a minimum of 240 credits
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of topological and geometric machine learning? Join the CIRCLE group at Imperial College London, led by Dr. Tolga Birdal, in a fully funded postdoctoral research role to lead transformative projects spanning
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(e.g., COBRApy, COBRA Toolbox, RAVEN). Demonstrated experience with machine learning methods and their application to biological or scientific data. Strong programming skills in Python, with experience
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. Required PhD in Computer Science / AI / Machine Learning Strong publication record in AI, ML systems, or related areas Strong programming skills in Python, C/C++ and experience with PyTorch, TensorFlow, JAX
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, Data Science, Machine Learning, or a closely related field. Strong programming skills in Python or MATLAB. Very good communication skills in English, both written and spoken, since the research
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at CERI under supervision of Dr. Goebel. and should contribute broadly to induced seismicity research. Specific research topics include seismicity analysis, machine learning, reservoir modeling, geothermal
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groundbreaking symbiosis of cutting-edge AI combined with human support. To learn more please visit https://www.kcl.ac.uk/research/embrace About the role The Research Fellow in Digital Health & Data Sciences is
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and modelling of omics, clinical and imaging data, development of reproducible pipelines, application of machine learning techniques, integration of multi-modal data, scientific publication and