79 development-"https:"-"https:"-"https:"-"Anglia-Ruskin-University" Postdoctoral positions at Argonne
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. Working within an interdisciplinary team, you will develop frameworks that connect atomistic features, mesoscale dynamics, and device-level performance. The effort will integrate heterogeneous data from
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The Applied Materials Division at Argonne National Laboratory has an immediate opening for a Postdoctoral Appointee. The candidate will be responsible for reviewing and developing design methods and
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The Materials Science Division (MSD) at Argonne National Laboratory is seeking highly motivated applicants for a postdoctoral appointee to join a multidisciplinary team developing next-generation
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We are seeking a highly motivated Postdoctoral Appointee with a strong background in artificial intelligence and machine learning (AI/ML), with particular emphasis on the development and application
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candidate would be a PhD in geophysical sciences, computer science, or machine learning with experience in developing and verifying deep learning-based models for large dynamical systems (e.g. weather
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modeling of x-ray spectroscopies sensitive to molecular chirality; simulations of x-ray–induced ultrafast electron-transfer, decay, and nuclear dynamics in gas- and liquid-phase systems; and the development
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for improvement, and/or analyze their impacts at individual, regional and national level. The candidate will also be tasked to develop new ideas into projects under the supervision of more experienced researchers
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on developing machine-learning surrogates for electronic structure and electrostatic potential and using these models to predict structural and electronic evolution under applied bias. Methods may include density
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In 2014, our team developed a compact proton linear accelerator (linac) design for an accelerator-driven system (ADS) aimed at nuclear waste transmutation, based on state-of-the-art niobium
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, machine learning, and control in the energy sector. The postdoc researcher will perform theoretical study and algorithm development on optimization/control/data analytics methods and authorize peer-reviewed