78 structural-engineering "https:" "https:" "https:" "https:" "Universidade do Minho CTAC" Postdoctoral positions at Argonne
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(CO2) conversion processes and contribute to engineering design of upscaled processes. The candidate will be a part of the Applied Materials Division (AMD) within AET at Argonne and will contribute
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materials from complex feedstocks to achieve the desired product quality and form. As a part of this team, you will: Apply electrochemical engineering principles to develop processes such as oxide reduction
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Requirements Required skills, abilities, and knowledge: Recent or soon-to-be completed PhD (within the last 0-5 years) by the start of the appointment in computer science, electrical engineering, applied
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School of Molecular Engineering, to publish results in peer-reviewed journals, and to present findings at conferences, symposia, and seminars. The candidate will keep current with relevant techniques and
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, you will: Apply engineering principles to develop molten salt synthesis and separations processes to support fuel cycle science and technology. Develop and test new electrodes for use in molten salt
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science. Position Requirements Ph.D. (completed or soon to be completed prior to the start of the appointment) in Physics, Materials Science and Engineering, Electrical Engineering, or a closely related
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to contribute to other large-team scientific projects in materials engineering, chemistry, and beyond at Argonne National Laboratory. Position Requirements Required skills: Recently completed PhD (within the last
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physics (HEP) and nuclear physics (NP) experiments. The successful candidate will be a key member of a multidisciplinary co-design team integrating materials science, computing, and device engineering to
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Science, Chemistry, Chemical Engineering, Electrical Engineering, Computer Science, Physics, or a related field Demonstrated proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow
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) simulations and reduced order modeling of turbulent and reacting flows relevant to advanced propulsion and power generation systems, such as gas turbines and detonation engines. The successful candidate’s