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with edge computing or embedded systems (e.g., NVIDIA Jetson, Raspberry Pi) Background in real-time processing and GPU acceleration (CUDA) Participation in relevant competitions (e.g., Kaggle, computer
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in cancers of unknown primary (CUP). Your Role You will join Subproject 3 (Model Alignment and Optimization), led by PD Dr. Keno Bressem (https://scholar.google.com/citations?user=wIEgwbkAAAAJ&hl=en
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University invites applications for a full-time, on-site PhD position. The position is funded through the LUMI AI Factory (EuroHPC) and focuses on scalable AI-for-science workflows using GPU-accelerated
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approaches, the application of meta learning, and the integration of convex optimization layers Increase inference efficiency (e.g., GPU acceleration) and assess the applicability domain of learned algorithms
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mathematicians, and domain scientists Develop software that integrates machine learning and numerical techniques targeting heterogeneous architectures (GPUs and accelerators), including DOE leadership-class
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About the role: The Costa Laboratory (https://profiles.imperial.ac.uk/t.costa ), in the Department of Life Sciences (https://www.imperial.ac.uk/life-sciences ), Imperial College London, invites
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information about the lab check out: https://www.moorelabstanford.com/ . About the role: The role will be in-person with hybrid flexibility and is a perfect opportunity for someone looking for a 1-year, fixed
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Fellow of AAPM. Details about Dr. Ren’s profile can be found at the following link: https://www.medschool.umaryland.edu/profiles/Ren-Lei/ Equipment includes a computer cluster with high-end GPUs, and state
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workflows, FAISS/embedding retrieval, LLM-based parsing, RAG-style pipeline, and GPU/HPC training. Familiarity with 3D data processing or willingness to learn quickly. Publications, thesis work
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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