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quantitative genetics, machine learning, bioinformatics, and population genetics, and their applications in an agricultural setting A modern dedicated computational infrastructure (CPUs & GPUs) Well-developed in
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in chemistry, physics, or related field. At least 2 years of experience developing quantum Monte Carlo algorithms. Strong problem-solving and analytical skills. Python programming experience. GPU
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the optimization of large-scale LLMs and deep learning architectures for biomedical research. Design and deploy high-performance AI systems using GPUs and hardware accelerators. Interact and collaborate
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free text of both biomedical literature and electronic patient records exploiting HPC, including GPUs embedded within NHS infrastructure. Development and deployment of ML operations software and tooling
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and a new GPU cluster. Opportunities for professional growth and career advancement. Collaborative and inclusive work environment that fosters creativity and innovation. Application of Domain Expertise
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software stacks, including GPU clusters and related computing resources. This position will also play a key role in designing and implementing new features for research projects. The successful candidate
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projects simultaneously. F3 Experience supporting application development for a variety of systems, e.g. Windows, Linux, MacOS, Android, iOS and hardware, e.g. GPU programming. E.g. with the data management
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 2 months ago
-site high performance/GPU compute facilities Competitive research in an inspiring, world-class environment A wide range of offers to help you balance work and family life Further training opportunities
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and model generation, point cloud rendering, visual effects (GPU shader, shadergraph, VFX) and 3D scene design Development of AR/VR applications What you bring to the table Full-time student at a German
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derived use cases by focusing on one or more of the following topics in their PhD project: Training and inference of ML models on GPU clusters. Method development for scalable and green AI. Use cases in