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» Chemical engineering Physics Mathematics » Applied mathematics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Norway Application Deadline 25 Jan 2026 - 23:59 (Europe/Oslo
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working. Eligibility criteria The candidates must provide a PhD diploma in Electronic Engineering, Telecommunications and Information Technologies or equivalent document issued by the doctoral school
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. The Department of Chemistry and Materials Science is looking for: A Doctoral Researcher (PhD student) in Machine Learning for Surface Structures The Data-driven Atomistic Simulation (DAS) group, led by
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physics, chemistry and applied science, have established active partnerships with TRIUMF, the Canadian Light Source, the Max Planck Society, University of Tokyo, and many other world leading institutions
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a M.Arch, MLA, or other terminal degree in Architecture, or a PhD in Architecture, Engineering, or a related field by the employment start date; and demonstrated potential to attract external funding
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
of geotechnical engineering. Required Qualifications: The ideal candidate will hold a PhD in Geotechnical Engineering, Civil Engineering, or a related field, and should demonstrate strong expertise in at least two
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, R., & Herrmann, H. J. (2016). Particle-Fluid-Structure Interaction for Debris Flow Impact on Flexible Barriers. Computer-Aided Civil and Infrastructure Engineering, 31(5), 323–333. https://doi.org
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, mechanical or biomedical engineering, material science, biochemistry, or a related field to apply. Candidates should have a PhD or equivalent degree and a record of academic excellence. Excellent communication
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/fimm/training-fimm/fimm-embl-international-phd-programme Research training at FIMM: https://www.helsinki.fi/en/hilife-helsinki-institute-life-science/units/fimm/training-fimm Doctoral programmes
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York University Abu Dhabi, seeks to recruit a highly motivated post-doctoral candidate in the areas of Artificial Intelligence (AI) for materials science, with an emphasis on structure-property