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Field
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address these in the cover letter): Machine Learning, Computational Simulations (e.g., CFD, FEA, etc.), domain expertise in Engineering problems, familiarity with High-Performance Computing (HPC
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papers, present results within the lab and at conferences, and help mentor students. Use and maintain lab resources on HPC and Github. Tools you will use daily include Python and R, version control (Git
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local research software engineer for your research group(s) and improve the use of computing among all group members. Stay up to date with the latest HPC, AI, and general computing/data management
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developing or applying parallel algorithms and scalable workflows for HPC resources. Experience developing or applying privacy-enhancing technologies such as federated learning, differential privacy, and
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purification and cryo-EM • Facilities: Glacios 200 kV Cryo-TEM, Phoenix HPC, Bragg Crystallography, Adelaide Proteomics Centre, plus 300 kV Titan Krios & Helios 5 UX cryo-FIBSEM via Monash Epigenetics & Genomics
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Implementation of scalable numerical algorithms on HPC architectures Excellent written and verbal communication and interpersonal skills. The ability to obtain and maintain a DOE Security Clearance Special
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machine learning software tools and frameworks Implementation of scalable numerical algorithms on HPC architectures Excellent written and verbal communication and interpersonal skills. The ability to obtain
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/kinematics; HNN or neural‑mass/spiking models; HPC. * Excellent scientific writing and communication in English. French is not required. Website for additional job details https://emploi.cnrs.fr/Offres/CDD
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computing (HPC). This position offers an exciting opportunity to work on cutting-edge research projects at the intersection of numerical linear algebra and advanced HPC. The candidate will join an
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computing and high-performance computing (HPC) environments. Interest in entrepreneurship, technology transfer, and translational research, particularly in AI-driven drug discovery and biotech startups