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optimization techniques and solvers (e.g., Gurobi, CPLEX), including linear, mixed-integer, or stochastic programming. Proficiency in at least one modern scientific programming language (Python, Julia, or C
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The Materials Science Division is seeking applicants for a Postdoctoral Appointee who will conduct cutting-edge research in AI for Materials Chemistry, with a focus on energy storage and conversion
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four staff members [Ian Cloët, Alessandro Lovato, Anna McCoy, and Yong Zhao] and several postdocs and students. The group has a broad research program in QCD/hadron physics and nuclear structure
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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 researcher to conduct independent research on foundation models for scientific and engineering applications, with an emphasis on training, adaptation
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physics. Familiarity with scientific programing languages such as python. Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long-Term (Fixed Term) Time Type Full time The expected
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: Contributes technical expertise through analysis and support for programs and projects associated with machine learning, HPC, and computational problems related to earth system science and other dynamical
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, which specialize for a restricted set of floating point operations only. Many scientific applications, particularly those that are physics-driven and mission-critical, still struggle to adapt to this new
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-generation nuclear science experiments at Jefferson Lab and the Electron-Ion Collider (EIC). As part of our growing multidisciplinary team, you will contribute to the development of superconducting nanowire
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programming language and contributions to open-source scientific software Good scientific productivity, as demonstrated by publications and conference presentations Effective oral and written communication