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. Experience in parallel programming (MPI, GPU, etc.). Proficiency in biostatistical methods. Ability to work independently and in group settings. Ability to learn quickly and apply new analytic techniques. Job
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them on massively parallel computers ? CPU, GPU, and APU systems. The successful candidate will work with Prof. Uri Shumlak and Prof. Jingwei Hu and contribute to a project that combines novel low-rank
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analysis, and GPU/FPGA-based acceleration. Ability to work in a multidisciplinary team, collaborate with industry and international partners, and contribute to the design of next-generation electron imaging
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allowance. Generous travel, equipment, and publication funds. Access to NYUAD’s world-class research facilities, including a high-performance computing (HPC) cluster with ~30,000 cores and 34 GPU nodes. Start
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an HPC cluster with ~30,000 computing cores and 34 GPU nodes. The position may start as early as September 2025. Applications will be accepted until the position is filled. To be considered, all applicants
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the models and algorithms on GPUs and mainframe computing platforms. Essential Function Yes Percentage of Time 40 Job Duty Mentoring graduate and undergraduate students. Assist the PI (Qi Wang) to mentor
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signal processing (GPU based) Proficiency in data analysis using Python, Matlab, or similar Self-motivating, independent-minded scientific researcher, effective collaborator Excellent written and oral
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equipped with GPUs. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR8197-VALHER-159/Candidater.aspx Requirements Research FieldBiological sciencesEducation LevelPhD or equivalent Research
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., TensorFlow, PyTorch). Practical experience with cloud computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications: Experience with multi-GPU model training and large-scale inference. Familiarity
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computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications Experience with multi-GPU model training and large-scale inference. Familiarity with modern AI environments and tools. Prior experience