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Field
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the computer science research conferences. Qualifications: PhD in computer science with file systems, GPU architecture experience. Proven ability to articulate research work and findings in peer-reviewed proceedings
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the team You will join the Thermal NDE Research Team within the Department of Computer and Information Sciences. The group hosts state‑of‑the‑art IR cameras, induction coils and GPU‑accelerated
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other scalable approximations. Experience running large-scale computations on supercomputers (e.g., SLURM job scripts, GPU acceleration, MPI communication). Notes: This is a full-time, 2 year
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approximations. Experience running large-scale computations on supercomputers (e.g., SLURM job scripts, GPU acceleration, MPI communication). Notes: This is a full-time, 2 year, postdoctoral appointment with
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access to substantial computational resources (GPU nodes), advanced high-throughput instruments (including a FACS, mass photometer, ITC, SPR, and others), and state-of-the-art characterization tools
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projects at CASS. The center fellows will have access to a 70,000-core Infiniband Cluster (Jubail) dedicated to the science division, several GPU-based clusters at NYUAD, and other supercomputer facilities
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(Jubail) dedicated to the science division, several GPU-based clusters at NYUAD, and other supercomputer facilities through the CASS network. NYUAD also has guaranteed observing time on the Green Bank
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and optimize large-scale training and inference runs for foundation models on JUPITER (multi-GPU/node, mixed precision, parallelization, I/O optimization) Integrate multimodal data sources (e.g., scRNA
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this project, we will develop neural diffusion techniques to design materials with targeted optical properties, scaling to large systems through efficient representations and GPU parallelization. We will also
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developing machine learning surrogates and emulators for dynamical systems. Proficiency in managing large datasets and training with GPU-enabled computing resources. Expertise in numerical optimization and