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understanding of parallel application development techniques (parallel programming models, algorithms, and software) Preferred Qualifications: Experience in implementing ab initio simulation codes such as VASP
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Associate to join the Parallel Systems Lab (https://psl-ntu.github.io ) at NTU’s CCDS. The role focuses on designing, developing, and evaluating efficient, scalable systems for modern multi-agent HPC-AI
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architecture of entirely new foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across
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foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across large GPU clusters on cryoSTEM
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. This activity will run in parallel with commercialisation activities by discussion with stakeholders for problem validation and obtaining performance requirement definitions. What We Can Offer You Committed
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common scientific programming languages such as C++, Python, and/or Julia and version control systems. Experience in parallel programming with one or more common parallel programming models, like MPI
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and plasmonic nanoparticles. You will contribute to both technical development and fundamental research. This may include improving parallelized optical detection, integrating optical tweezers with
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restricted access regimes – ZRR – as defined in Article R413‑5‑1 of the French Penal Code, or to sensitive units) may have consequences: on the timeframe for establishing the contract, due to parallel
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systematically with several stakeholders and parallel activities. The following experience is particularly advantageous: Implementation research and use of established frameworks, particularly PRISM and/or RE-AIM
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information on changes in core temperature and the influence of relevant physiological variables during exposure to varying thermal environments. The Research Fellow will collaborate closely with a parallel PhD