63 parallel-computing-numerical-methods-"DTU" Postdoctoral positions at Oak Ridge National Laboratory
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the Integrated Building Deployment and Analysis Group in the BTSD, ESTD at Oak Ridge National Laboratory (ORNL). The IBDA group leads the development of innovative methods for residential and commercial whole
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liquids, frustrated magnetism, excitonic magnets, and strongly correlated electron systems. You will work closely with theorists, experimentalists, and computer scientists to build robust, scalable
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Requisition Id 15604 Overview: The National Center for Computational Sciences (NCCS) at the Oak Ridge National Laboratory (ORNL) is seeking a postdoctoral research associate in High-Performance
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phenomenological and/or computational methods for quantum/classical dynamics in complex system. Preferred Qualifications: Rich experience with modeling in spin or atomic dynamics will be highly advantageous. Basic
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Requisition Id 15584 Overview: Do you have a passion for applying AI methods for accelerating scientific discoveries and an ability to think outside of the box in a collaborative and open
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environmental conditions, and predicting photosynthesis at multiple scales. The selected postdoctoral scientist will work with a team of mathematicians, computational scientists, plant geneticists and
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of formulation, coating methods, and carbonization/sintering process, as well as the design of novel vitrimers for adhesives and fiber reinforced composites. This position resides in the Soft Materials and
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breeding blankets, including computational fluid dynamic (CFD), thermal hydraulic, and magnetohydrodynamic (MHD) analyses. We seek individuals with advanced analytical and computational skills who can use
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working with trace metals Experience with materials characterization and analysis methods. Excellent written and oral communication skills. Motivated self-starter with the ability to work independently and
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, transportation, and more, with a special emphasis on grid resilience assessments and equity analysis. You will have the opportunity to creatively use interdisciplinary methods from computational data science