587 engineering-computation "https:" "https:" "https:" "https:" "UCL" "Brunel University London" PhD research jobs
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, the candidate will engage with U.S. ATLAS program office and management team to insure the continuation of the University of Pittsburgh's participation in software development and support on behalf of the ATLAS
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orientations and gender identities, as well as from all qualified candidates with the skills and knowledge to productively engage with diverse communities. McGill implements an employment equity program and
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use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission analysis, and infrared thermography. Industry
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. Requirements: Minimum: Ph.D. in Mechanical Engineering, Materials Science, Computer Science, or related field; expertise in additive manufacturing, materials design, or AI/ML; strong publication record
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The Faculty Social Sciences & Solvay Business School, Department Business Technology and Operations, Research Group House of Sustainable Transitions is looking for a PhD-student with a doctoral
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Université Paris-Saclay. Job profile: • Researcher in theoretical/computational condensed matter physics. • Strong proficiency in programming and genuine interest for numerical methods • Solid background in
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. in Physics, Materials Science, Electrical Engineering, or a related field by the start date. Preferred Qualifications: Hands-on experience in nanofabrication techniques (e.g., electron-beam lithography
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of research experience; OR master's degree and two (2) years of research experience. Preferred Qualifications: Ph.D. in Geography, Environmental Sciences and Engineering or equivalent with emphasis on Flood
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, finance or computing science/natural language processing/machine learning. Preference will be given to those who are proficient in Python, adept at processing large-scale data and have worked with large
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the context of critical illness. This position focuses on computational modeling of host-response mechanisms using high-dimensional multi-omics datasets. The fellow develops novel computational pipelines