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7 Sep 2026 Job Information Organisation/Company NTNU Norwegian University of Science and Technology Department Department of Computer Science Research Field Computer science Researcher Profile
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 5 days ago
management, or storage integration * Databases, data platforms, distributed systems, GPU-enabled computing, or MLOps workflows * Experience providing technical leadership, mentoring developers, or owning major
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of computational systems biology and mathematics/statistics with a strong attitude to open research software development. For more information visit http://www.fz-juelich.de/ibg/ibg-1/modsim or http://github.com
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, mathematical sciences, physical sciences, and interdisciplinary research areas. Research computing needs vary significantly across these areas, including CPU-intensive workflows, GPU and AI/ML workloads, data
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dedicated GPU-equipped computing workstation and data-storage resources; - access to molecular-modeling and chemoinformatics software; - resources for the acquisition and experimental evaluation
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2026 - 00:00 (UTC) Country United Kingdom Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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practices and international standards. Leverage VIB Data Core services, including high-performance computing pipelines and large-scale GPU resources, to scale ML development and deployment. Your profile PhD
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resources. Working knowledge of NVIDIA-specific technologies relevant to research computing, such as GPU-enabled workflows, CUDA-enabled tools, GPU resource use, or AI/ML computing environments. Basic
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Challenge grant. The successful candidate will work closely with the Principal Investigators (PIs) to develop and implement innovative research integrating machine learning, computer vision, and wildlife
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is available at https://colalab.ai/ . At EI, the group will develop an ambitious Generative Digital Biology (GDB) programme, developing multimodal, cross-organism and experimentally grounded AI systems