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Field
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, implementing input sanitization, and contributing to AI‑safety research. Utilizing GPU/TPU resources, mixed‑precision training, and distributed training frameworks such as DeepSpeed or ZeRO. Prior work
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or research experience in computer vision or machine learning. • Experience optimizing models for real-time inference on edge and embedded platforms using techniques such as quantization, pruning, and GPU
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 2 months ago
, mathematics or any related field; correspondingly, Postdocs hold a PhD or equivalent degree in the above mentioned fields. What we offer State-of-the-art on-site high-performance/GPU compute facilities
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for embedded and GPU platforms. Collaborate with ARSPECTRA engineers and surgeons to create a complete AR guidance pipeline : tracking, SLAM, gaze, user interface Your profile PhD in machine learning
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physics, mathematics or any related field; correspondingly, Postdocs hold a PhD or equivalent degree in the above mentioned fields. What we offer State of the art on-site high performance/GPU compute
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benchmark them with a realistic case study. The main focus of the project can develop either more in the mathematical theory of MCMC, the implementation of code for the Jülich supercomputers (GPU/CPU
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(OMOP CDM, FHIR) or metadata harmonisation Experience with ETL tools, workflow engines, or bigdata frameworks (e.g., Spark, NiFi, KNIME) Familiarity with containerisation (Docker) and HPC or GPU computing
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models on GPU-based systems; familiarity with HPC environments is an advantage Interest in interdisciplinary research at the interface of AI and genomics; prior experience with biological data
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for mechanical, electrical, cooling, and infrastructure systems that underpin Cornell’s computing environment, including High-Performance Computing (HPC) and Graphics Processing Unit (GPU)‑intensive workloads
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made at the Postdoctoral Research Associate rank. The AI Postdoctoral Research Fellow will have access to the AI Lab GPU cluster (300 H100s). Candidates should have recently received or be about to