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We are seeking a highly motivated Postdoctoral Appointee with a strong background AI/ML specifically in the development and application of Large Language Models (LLMs) tailored for scientific use
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Knowledge in modeling and algorithms for large-scale ordinary differential equations (ODEs) and differential-algebraic equations (DAEs) Proficiency in a scientific programming language (e.g., C, C++, Fortran
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scientific programming language Experience with ML software such as Tensorflow and PyTorch Experience with ATLAS Software Development Ability to model Argonne’s core values of impact, safety, respect
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candidate will work on cutting-edge research integrating genome-scale language models (GenSLMs) with deep mutational scanning data, and experimental virology to predict viral evolution and identify emerging
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) or equivalent experience in a computational science discipline, computer science, or in a related field Strong programming skills in one or more scientific programming language, such as C++ and Python Experience
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language. Familiarity with version control (Git) and containers (Docker/Podman). Familiarity with DER modeling and OpenDSS. Interested candidates should submit: A detailed CV. A cover letter describing your
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interaction with complex data. The candidate will advance techniques in visualization, data analysis, and high-performance computing (HPC), integrating artificial intelligence (AI) and large language models
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energy physics, physics, and computational science Programming expertise in C/C++, Python, Fortran, or another scientific programming language Comprehensive knowledge of Input/Output and data persistence
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, safety, respect, integrity, and teamwork. Preferred Knowledge, Skills, and Experience Basic knowledge of a programming language. Experience with surface science sample preparation techniques. Experience
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. Knowledge of C/C++ language and parallel programming with MPI. Background in modeling of engineering systems. Familiarity with high performance computing (HPC) software platforms is a plus. Skills in using