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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
interdisciplinary center for research and education in quantitative genetics and quantitative genomics (http://www.qgg.au.dk/en). QGG is an international organization with 70 employees and visiting researchers from
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interdisciplinary center for research and education in quantitative genetics and quantitative genomics (http://www.qgg.au.dk/en). QGG is an international organization with 70 employees and visiting researchers from
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infrastructure, providing trainees with access to UF’s HiPerGator supercomputing facility, including 50 NVIDIA B200 GPUs, and a high-throughput automated screening platform. We offer a supportive, collaborative
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engineering. The work involves simulations for quantum error correction and mid-circuit operations, and will require both low-level optimization skills (e.g., SIMD, GPU, FPGA) and an understanding of quantum
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. This project seeks to overcome key workflow and precision limitations in HDR brachytherapy by enabling real-time adaptive optimization during needle insertion, integrating live ultrasound imaging with GPU
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options Employee and dependent educational benefits Life insurance coverage Employee discounts programs For detailed information on benefits and eligibility, please visit: http://uhr.rutgers.edu/benefits
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data from the European XFEL facility at DESY. Project website: https://www.mpinat.mpg.de/628848/SM-Ultrafast-XRay-Diffraction Your profile Eligible candidates have strong skills in computational physics
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experimental data and workflows. The team drives innovation in algorithm design, GPU-accelerated computing, and quantum-ready methodologies applicable to complex scientific problems across the experimental
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-of-the-art compute and GPU infrastructure, including H100 and B300 GPU clusters. Innovation: The opportunity to apply a recently published, "proof-of-concept" method for synthetic enhancer design to a critical
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research practices Experience training and deploying machine-learning models on GPU-based systems; familiarity with HPC environments is an advantage Interest in interdisciplinary research at the interface