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or manufacturing systems. Experience with data analysis, modeling, or automation using tools such as Python, MATLAB, C#, C++, or similar engineering software environments. Experience with CAD/CAM/CAE tools such as
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integrating these paradigms into unified compilation and optimization strategies. Programming Languages & Frameworks: Experience with Julia, Rust, Python, Kokkos, OpenSHMEM, or similar emerging ecosystem tools
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, including parallel computing frameworks, C/C++, Julia and/or python Experience with training AI surrogate and/or inverse models Experience working in underground laboratories and/or clean rooms Excellent
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depth with project delivery. Strong proficiency in automation and infrastructure-as-code frameworks (Ansible, Puppet, Salt). Advanced scripting or programming skills (Python, Bash, Go) for automation and
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., Python or R; reproducible workflows; version control) Experience or interest in AI/ML application to ecophysiological research Preferred Qualifications: Hands-on experience with lab/growth chamber and/or
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. Experience in multiple scientific programming languages (Python, Julia, Fortran, C++, AI etc.) Excellent written and oral communication skills. Motivated self-starter with the ability to work independently and
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Context Protocol (MCP) or comparable orchestration/integration patterns Proficiency in Python and backend system design Experience with containerization and deployment (Docker, Kubernetes) Preferred
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Qualifications: Excellent interpersonal/communications skills, and the ability to work as part of a team. Experience implementing and maintaining highly available systems/services. Experience with PHP, Python
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Qualifications: Ph.D. (within 0–5 years) in computational bioscience, computational biophysics, computer science, or a related field Strong programming skills in C++, Python, or similar scientific computing
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clearance, DoD TS with SCI and Poly Understanding of multidimensional and tabular modelling, vector databases, Graph DB. Experience using Microsoft Visual Studio or Visual Studio Code, Python, PyTorch