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Field
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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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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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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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and their communities. Examples of software project applications of CCA researchers include fluid dynamics and plasma simulations, radiative transfer, N-Body & dynamical simulations, GPU & other high
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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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. 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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parallel/GPU computing. Job Duties Job Duty Doing research problems in the area of mathematical foundations of data science and machine learning. The postdoc will assist with ongoing research projects
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challenge the status quo. At Jane Street, you will work alongside a tight-knit team, utilizing petabytes of data, our computing cluster with hundreds of thousands of cores, and our growing GPU cluster
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conferences. Qualifications: PhD in computer science with file systems, GPU architecture experience. Proven ability to articulate research work and findings in peer-reviewed proceedings. Knowledge of systems