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language and compiler ecosystems to accelerate scientific software development at scale. Major Duties/Responsibilities: Agentic AI for High‑Productivity Languages: Develop multi‑agent reasoning systems
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. Experience with large language models, natural language processing, and generative AI tools Self-disciplined work ethic and eagerness to tackle challenging research problems. Experience with heath care
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portability programming language (e.g., CUDA, HIP, Kokkos, SYCL). Special Requirements: Q Clearance: This position requires the ability to obtain and maintain a clearance from the Department of Energy. As such
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compliance-driven or DOE-regulated environments. Facility with AI and large language models (LLM) tools to support analysis, documentation, reporting, and knowledge integration, consistent with data security
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). Experience with shared and distributed memory parallel programming models such as OpenMP and MPI. Experience with one more GPU or performance portability programming language (e.g., CUDA, HIP, Kokkos, SYCL
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stakeholders on time and on budget. Excellent written and verbal communications skills, including the ability to accurately translate complex science and engineering concepts into non-specialist language
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/Responsibilities: Organize technical information from various BER research topics into a cohesive unit and produce written material in clear language without loss of technical content. Oversee and coordinate efforts
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Qualifications: Current experience writing software. Most relevant languages: C, C++, Python, and Java. Basic binary literacy is important. This includes understanding how software is architected, language
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configuration management and automation tools such as Git, Jenkins, Ansible, or Puppet. Moderate proficiency in at least one scripting language such as Bash, Python, or others. Experience performing advanced
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experience. Understanding of biogeochemical and ecological processes. Programming experience in Fortran, python, R, or a related language. Experience in geospatial and/or time series data analysis. Evidence of