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advanced compilation techniques for scientific and AI applications on heterogeneous GPU clusters. Research topics include scheduling, memory management, communication–computation overlap, and performance
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modeling, and AI experts, as part of the international project M2 LInES (https://m2lines.github.io) . You can read about some of our recent work here: Dheeshjith et al. 2025 , Duncan et al. 2025 , Pedersen
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research directions while collaborating with a team composed of domain scientists, experts in climate physics and modeling, and AI, as part of the international project, M2 LInES https://m2lines.github.io
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100% funding per SNSF guidelines (~CHF 90'000/year) Access to modern GPU clusters and confidential-computing infrastructure Collaboration with leading researchers in AI & HPC systems and digital health
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variety of computational devices (e.g. CPUs and GPUs) while ensuring overall consistency and performance. - contribute to identify new CSE applications domains, such as condensed matter systems, quantum
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managing supercomputer resources Strong skills in algorithm development for large sparse matrices Excellency in programming GPU accelerators from all major vendors Very good command of written and spoken
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Methods, LBM), and HPC. For a selection of possible research areas, see: https://www.math.cit.tum.de/math/forschung/gruppen/numerical-analysis/research/ Responsibilities: Development and analysis of new
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/TimeSformer, CLIP/BLIP or similar) in PyTorch, including scalable training on GPUs and reproducible experimentation. Demonstrated experience building explainable models (e.g., concept bottlenecks, prototype
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Appointment Term: 1-2 years Appointment Start Date: January 2026 Group or Departmental Website: https://greiciuslab.stanford.edu/ (link is external) How to Submit Application Materials: Please email application
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-changing technologies. Life-changing careers. Learn more about Sandia at: https://www.sandia.gov *These benefits vary by job classification. What Your Job Will Be Like: We are seeking a Postdoctoral