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- MOHAMED BIN ZAYED UNIVERSITY OF ARTIFICIAL INTELLIGENCE
- Mohamed bin Zayed University of Artificial Intelligence
- NEW YORK UNIVERSITY ABU DHABI
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for better training and novel network designs. Low Effective-dimensional Learning Models. We will extend foundational theory of how large ML systems can be regularised to have dramatically fewer trainable
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, information and communication sciences, anthropology, history, and geography. This teamwork will be carried out within the framework of INRAE's national viability network. The successful candidate will benefit
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for training large-scale cryoSTEM foundation models. Project Leadership: Manage complex research sub-projects and ensure research milestones are met. Mentorship: Guide and mentor graduate students and junior
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. Project Leadership: Manage complex research sub-projects and ensure research milestones are met. Mentorship: Guide and mentor graduate students and junior researchers within the lab. Academic Output: Author
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Engineering. NYU Abu Dhabi, NYU New York, and NYU Shanghai, form the backbone of NYU’s global network university, an interconnected network of portal campuses and academic centers across six continents
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on the design and development of mathematical, probabilistic, and statistical frameworks for drawing inferences from complex biological data in collaboration with scientists at the Snow Centre for Immune
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interested in candidates working in the following research areas: -- arithmetic algebraic geometry and the BSD conjecture, -- Langlands program and related problems, -- algebraic geometry and complex geometry
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The position will involve developing new mathematical/computational methods at the intersection of scientific computing and machine learning. At a high level, the project is to build neural network models
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research program in Artificial Intelligence (AI) and Mathematics. This position involves applying machine learning tools, particularly reinforcement learning (RL), to address complex research-level
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for this position: differential equations, operator spectral theory, linear vector spaces, differential geometry, boundary-value problems, Green's functions, variational techniques, and complex analysis