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research computing ecosystem spanning on-premises and remote-site infrastructure, including: • HPC compute platforms for research and data-intensive workloads • GPU-enabled environments for AI and machine
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inclusive workforce Access to our GPU-accelerated HPC cluster and laboratories with cutting-edge sequencing technologies and molecular assays Performance-based remuneration and other benefits The opportunity
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compensation package with comprehensive health and welfare benefits. A supportive team environment that promotes collaboration and knowledge sharing. Access to world-class computational infrastructure, GPU-based
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with direct clinical relevance Access to large-scale multimodal biomedical datasets and modern GPU infrastructure Close collaboration with clinicians, biologists, and AI researchers in a highly
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, Z. Ye, P. Sun, X. Wang, Y. Luo, T. Zhang, and Y. Wen, “Deep learning workload scheduling in gpu datacenters: Taxonomy, challenges and vision,” arXiv preprint arXiv:2205.11913, 2022. [5] J. Lin, W.-M
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, Vehicular Communications Experience in system modeling and simulation of communication systems Strong programming skills in MATLAB are required; experience with Python, C/C++, or GPU-based computing is an
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community. We provide the resources to match your ambition: Industrial-Scale Computing: Exclusive access to massive GPU clusters and high-performance computing. Guaranteed Talent Pipeline: Generous
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-node GPU training and inference pipelines for foundational models. You'll also develop tools for ingesting, transforming, and integrating large, heterogeneous microscopy image datasets—including writing
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/ computer vision and pattern recognition, including but not limited to biomedical applications Strong interest in applied machine learning, including but not limited to deep learning Experience utilising GPU
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finite-element models, e.g. Poisson, linear elasticity, large-deformation soft tissue, for real-time execution on AR devices and GPUs Implement these models within open-source frameworks such as SOFA