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Your tasks Contribute to the projects in the group at the intersection of programming languages, software engineering, and security Collaborate with the other group members Extend the theoretical
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, Mechanical or Electrical Engineering, Control, Applied Mathematics, or a related field. You should have a solid foundation in machine learning and strong programming skills (Python, deep learning
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will include: Assemble and validate modular electrocatalytic reactors and analysis methods for realistic CO2 electrocatalysis, with a focus on parallel investigations and accelerated aging. Dissect
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released models Make evaluations run quickly and at scale: parallel execution on Alps, efficient use of inference backends, caching, and result tracking Reduce mismatch between evaluations during
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/aarch64 platforms Familiarity with HPC networking and communication stacks: Slingshot, libfabric, NCCL and its debugging Experience with parallel filesystems (e.g. Lustre) and storage performance tuning
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scientific excellence in the areas of vector query processing, serverless/just-in-time query execution, parallel and distributed data management, and data management systems on emerging hardware Passionate
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programs in parallel. Please check this page for additional information. Please note that this is a separate application process necessary to be eligible to complete your PhD at EPFL. Potential doctoral
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Diplomas Transcripts/grades from Bachelor’s and Master’s studies If you are successful, you will need to enrol in one of the EPFL doctoral school programs in parallel. Please check this page for
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Strong written and spoken communication in English and German Ability to work independently and manage multiple parallel projects Interest in ophthalmology, retinal diseases, or translational clinical
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system for thin, durable structural interventions. It can be deployed through conventional casting for standard applications and through 3D printing for complex or non-planar geometries. In parallel