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navigation algorithms and machine learning models on physical robot platforms. We are particularly interested in candidates with expertise in generative AI and curriculum learning applied to robotics, as
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principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with several national and international research groups, edits one of the major
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to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a
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invites applications for a Post-Doctoral Associate position, in the area of Quantum Algorithms. The candidate is expected to conduct research in computer science focusing on the combinatorial aspects
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research for understanding the learned algorithms in brains and machines. The post holder will provide guidance to less experienced members of the research group, including postdocs, research assistants
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Infrastructure? No Offer Description Research line: Learning in single cells through dynamical internal representations. Job description: Develop theory, models and algorithms for identifying molecular encodings
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applications for a Postdoctoral Researcher position. The selected candidate will undertake both collaborative and self-directed research on mathematical modeling, optimization and simulation models/algorithms
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various processes in modern machine learning, including learning, inference, and generation. In particular, we are working to establish novel theories and algorithms that enhance the efficiency
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with signal processing and control algorithms. Excellent communication skills in English (written and spoken); ability to work in interdisciplinary teams and to publish scientific results. A strong
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of single-cell molecular data. Experience and expertise in ML/AI algorithms for analysis of single-cell genomic data Demonstrated capacity to work collaboratively with researchers across both dry and wet