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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
balance Training and international experience in public–private partnerships Mentoring for career development Access to high-performance computational resources (with GPUs) A collaborative environment
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balance Training and international experience in public–private partnerships Mentoring for career development Access to high-performance computational resources (with GPUs) A collaborative environment
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-end GPUs We will jointly choose tasks based on your expertise and interests. Most important is a strong interest in scientific methods, a solid knowledge foundation (e.g. studying computer science, open
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. In addition, CVI2 provides high-performance GPU computing resources that support the design and training of advanced AI models. The research agenda of CVI2 focuses on cutting-edge topics such as 3D
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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 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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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
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RTDS. Experience with software development. Experience with use of GPUs, multi-core CPUs, advanced computing (e.g., QPUs). Excellent written and oral communication skills. Motivated self-starter with
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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