32 parallel-computing-numerical-methods "DTU" Postdoctoral positions at Aarhus University
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The Department of Media and Journalism Studies within the School of Communication and Culture at Aarhus University invites applications for a postdoctoral position in digital methods and the creator
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., programming language theory, formal methods, or algorithms/optimization) and be open to practical computational experiments. PostDoc applicants must further demonstrate a solid history of academic writing and
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substantial knowledge and research experience in areas such as computational fluid dynamics, turbulence modeling, data-driven methodologies, machine learning, and parallel computing. The candidate should also
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graph algorithms for optimization under physical constraints Applying graph mining and graph data management techniques Designing computational methods for waste heat reuse and green transition goals
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This is a full-time (37 hours/week) on-site role located at Åbogade 34, 8200 Aarhus N, Denmark for a Postdoctoral Fellow at the Department of Computer Science, Aarhus University. The postdoctoral
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with experimental or computational methods for studying the failure of complex and heterogeneous materials. You have demonstrated the ability to publish in high-quality international journals and to
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Hopkins University (USA). About the role The PDRA will advance next-generation mapping methods for equitable and intelligent epidemic surveillance, contributing to the development of scalable GeoAI systems
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microscopy, optical interferometry, vacuum technology, finite element method simulations will be involved. Applicants should hold a PhD in Physics, Nano-science, Engineering or similar, experience with optics
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otolith-based method and relate FMR to oceanographic and ecological conditions along north-south and fjord-offshore gradients in East Greenland. Experience with isotope analyses and arctic field work
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: Experience with numerical climate models and/or chemical transport models such as CESM and/or GEOS-Chem. Advanced programming skills in Python, Fortran, or other relevant languages. Experience in wildfire