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. Understanding of local hardware optimization (GPU/VRAM management). Comfortable putting together a simple working interface for a workflow (e.g. Gradio) — no formal UX/UI design background required. Able
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computing environments and GPU computing. Proven experience in weather and climate models development and applications. Experience in machine learning, deep learning, or AI applications for atmospheric
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, AI agent orchestration platforms and GPU-enabled AI infrastructure. Responsibilities: Platform operations and reliability Own day-to-day operations of SEA-LION API Farm, our multi-cloud LLM inference
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the thermal process from GPU computation to radiative cooling Integrate the algorithms into a larger computational satellite simulation environment Identify new cyber-physical systems research topics related
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distributed training concepts, GPU-based training, checkpointing, experiment tracking, training stability and compute optimisation. MLOps, infrastructure and deployment: Familiarity with Linux environments
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-performance computing (HPC) clusters or cloud GPU instances. Analytical Rigor: Ability to design ablation studies to isolate the impact of individual loss components. Communication: Ability to clearly
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well as large-scale GPU computing facilities for deep learning. Our Lab aims to hire a Research Associate to support the Project Lead on the development of adversarial robust large vision language models. Key
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infrastructure--- including GPU-enable units and HPC server Manuscript and grant preparations --- for all research pertaining to mental health NLP and behavioral work. And to support grant administration, co
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topics related to the position. Experience with data management, HPC and GPU is a plus. They should also demonstrate the ability to work effectively in a multicultural, interdisciplinary team at EOS and
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, and guidelines to ensure continued relevance and effectiveness. Evaluate incoming resource and procurement requests (e.g. GPU workstations, servers, and cloud credits) in compliance with university