51 postdoc-in-thermal-network-of-the-physical-building Postdoctoral positions at Argonne
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algorithm development in conjunction with extensive applications in the fields of nanoscience and energy-related materials. Position Requirements a PhD in physics, or closely related field. Degree must have
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the goal to enhance predictive capability and scalability of multi-scale and multi-physics simulation codes. The prospective postdoctoral appointee will perform multi-physics and multi-scale CFD simulations
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The Buildings & Industry Group within the Energy Systems and Infrastructure Analysis (ESIA) Division at Argonne is seeking to hire a postdoctoral appointee to conduct research and modeling-based
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The Applied Materials Division (AMD) in the Emergent Materials and Process Group at Argonne National Laboratory in looking for a Post-doctoral Appointee -- Pyrometallurgy. The candidate will perform
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simulation of x-rays involving their propagation through beamline optics, scattering from the sample, coded aperture, and ultimately their recording at the detector. This eDort will build on ongoing work
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Facility (MERF), a pre-pilot-scale research and development facility well-equipped for process development, scale-up, and prototyping. The Postdoctoral Appointee will be responsible for integrating materials
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mechanisms through reaction kinetics analysis and other physical organic and inorganic techniques Perform detailed in situ / operando studies of catalysts using X-ray Absorption and Emission Spectroscopies
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, networking, and leadership. Position Requirements Required Knowledge, Skills, and Experience: This level of knowledge is typically achieved through a formal education in economics, operations research, public
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fundamental understanding of reaction mechanisms in molten salts and apply insights to process development and scale up. Project activities will include the design and development of online monitoring tools
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contributions in: Building novel generative models for predicting genome-scale evolutionary patterns using GenSLMs Developing scalable models that can, when integrated with high throughput molecular dynamics