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Field
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using tools such as LabVIEW, Python or MATLAB. Pre-employment checks and declarations Your employment is conditional upon the successful completion of all pre-employment or background checks required
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instrumentation. Experience with Python, model/API integration, retrieval-augmented generation, tool-using agents, scientific databases, and automated experimental platforms is highly desirable. The candidate is
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holds a Ph.D. in Chemical Engineering (or a related field), is proficient in both mechanistic modeling and ML frameworks (e.g., TensorFlow, PyTorch), and has strong programming skills (Python/MATLAB/C
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design and printing. • Metamaterial design and analysis, preferably with strong expertise in COMSOL Multiphysics. • Strong programming experience: C++, Matlab, Mathematica, Python. • Publications
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Scientific computing using FEniCS, COMSOL, and Python/C++ KAUST offers a highly international and interdisciplinary research environment with access to world-class computational and experimental facilities.
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language (C++, Python, Rust, …) One high-quality first-author paper (journal or top-tier conference) You are expected to be somewhat accustomed to teaching, and to demonstrate good potential within research
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background in mathematical optimization and modeling • Excellent programming skills (Python, Matlab, Julia, or similar) • Interest in energy systems, electric mobility, and battery technologies • High level of
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Science, Physics, Mathematics or Computer Science. You have a solid background in computational fluid dynamics (CFD) and be proficient in programming (e.g., Python, Fortran, or C++) and visualization tools
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modeling codes (e.g., FISPACT-II, TALYS), cross-section evaluations, and programming in Python and C++. 06/24/2026
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the use of machine learning for regression tasks. Demonstrated proficiency with Python or similar scientific programming environment. Ability to work with large datasets, develop reproducible workflows and