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experimental data. Experience in GPU programming. Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long-Term (Fixed Term) Time Type Full time The expected hiring range for this position is
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research in ML for Health, including HIPAA-compliant compute infrastructure with high memory GPUs and access to Stanford Healthcare data, which includes EHRs for over 5M patients and 100M clinical notes
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++ and Python programming languages. Experience in open source projects, GPU programming, distributed computing and cloud computing are considered to be strong assets. The position of Research Fellow at
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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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hardware architectures (multicore, GPUs, FPGAs, and distributed machines). In order to have the best performance (fastest execution) for a given Tiramisu program, many code optimizations should be applied
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structure, novel electronics and bioengineering applications. AI Postdoctoral Research Fellows will have access to the AI Lab GPU cluster (300 H100s). Candidates should have recently received or are about to
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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
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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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electricity prices with focus on Nordic electricity market including implementation, test and validation at the DTU Risø HPP facility (possibly in a GPU computing infrastructure) Aid the implementation of IEA
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be direct access to advanced biophysical infrastructure in the biophysics core facility headed by the PI, a GPU cluster with working pipelines for computational design and the department’s bioimaging