63 experiment-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" Postdoctoral positions at Argonne
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field. Strong computational chemistry background in atomistic simulations, electronic-structure theory, DFT, structure-property relationships, and interpretation of simulation results. Hands-on experience
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solid electrolytes. We are seeking candidates who will be able to design experiments and develop methodologies to design material compositions, ink rheological properties, and coating and drying process
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experience Strong background in atmospheric dynamics, turbulence, land–atmosphere interactions, cloud physics, or precipitation processes Experience working with large observational or model datasets
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molten-flux growth (metals, chalcogenides, halides, and hydroxides), Bridgman crystal growth, chemical vapor transport, and related methods. 2. Hands-on experience with materials characterization
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field at the Ph.D. level with zero to five years of employment experience. Demonstrated experience in leading research initiatives, with a strong track record of publishing in peer-reviewed journals
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should have technical experience in vehicle (on road, offroad, rail or marine) modelling, systems analysis, techno-economic analysis of vehicle systems. Prior experience in carrying out simulations
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developing advanced AI/ML models for applications in physics, chemistry, or materials science Experience with periodic simulation codes such as VASP Proficiency in Python programming Excellent written and oral
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of Chemical Engineering, Mechanical Engineering, Materials Science, Chemistry, or a related field A deep understanding of electrochemistry, electrochemical engineering, and battery science Strong experience in
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of advanced bioleaching processes for recovery of critical minerals from secondary materials The candidate will design and execute experiments; operate, monitor, and troubleshoot bench- and pilot-scale
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learning, statistical modeling, or advanced analytics applied to complex industrial, energy, logistics, manufacturing, or supply chain systems. Experience developing and applying optimization models, such as