Sort by
Refine Your Search
-
optimization for heterogeneous distributed data, and hardware/software codesigned engines for demanding applications. Main duties and responsibilities Work closely with all members of the lab carrying out
-
, and model adaptation strategies. Scalable AI training: distributed training, efficient fine-tuning, evaluation, and deployment on large-scale compute. Multimodal learning: representation learning and
-
quantitative and probabilistic extensions, and scalable verification via symbolic automata and related decision procedures Routing algebras: composable, algebraic representations of distributed
-
research; Experience with quantitative data analysis and proficiency in one or more programming or scientific computing environments, such as Python, R, or MATLAB; A strong publication record appropriate to
-
intersection of applied physics, high-performance computing, and semiconductor metrology. The successful candidate will have the opportunity to develop their own independent research direction and work
-
member of the SNSF Starting Grant project NEXUS-3D, working at the intersection of applied physics, high-performance computing, and semiconductor metrology. The successful candidate will have the
-
participation in the annual team meetings held in the case-study cities. Access to the computing infrastructure and to the resources of EPFL, including the Excellence in Africa Center (EXAF). A central