13 computational-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"FEMTO-ST" Postdoctoral positions at Argonne
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The Chemical Sciences and Engineering Division invites applications for a Postdoctoral Appointee to conduct computational research focused on transition metal-containing clusters for the
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The Chemical Sciences and Engineering Division invites applications for a Postdoctoral Appointee to contribute to innovative research at the intersection of computational catalysis, quantum chemistry
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facilities in partnership with the computational science community. We help researchers solve some of the world’s largest and most complex problems with our unique combination of supercomputing
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position will focus on ultrafast dynamics in femto- to nanosecond time-domains in quantum materials including nonequilibrium phase transitions and collective excitations in quantum materials
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availability. Relevant Publications: 1. P. Chen et al., Ultrafast photonic micro-systems to manipulate hard X-rays at 300 picoseconds, Nat Commun, 10:1158 (2019). https://doi.org/10.1038/s41467-019-09077-1. 2
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Position Overview We are seeking a Postdoctoral Appointee to join the Computational Science and Artificial Intelligence Group in the X-ray Science Division of the Advanced Photon Source (APS) at
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platform for X-ray absorption spectroscopy by integrating LLMs, scientific machine learning, physics-aware workflows, and strong computational chemistry/electronic-structure expertise. The researcher
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phenomena. The selected candidate will develop computational models at the mesoscale and/or macroscale based on the principles of mass, momentum, and energy conservation to describe processes such as
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/reactions, with increasing emphasis on using artificial intelligence and quantum information science. The group has access to extensive laboratory and national computational resources and has significant
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ideal for someone who enjoys working at the intersection of data science, machine learning, materials research, and experiment, and who is motivated to translate computational advances into real