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Communications AI & Computing (https://www.nature.com/commsaicomp/ ). Communications AI & Computing is a multidisciplinary open-access journal publishing high-quality research across computational sciences and
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: The design and analysis of computational methods that accelerate AI/ML when applied to large scientific data sets; Energy efficient physics-aware algorithms, capable of distributed learning on high performance
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include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a travel allowance and access to advanced
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. Expertise is required or highly desired in one or more of the following areas: algorithms, analytical derivation, data analysis, coding, or mathematical modeling. Strong programming skills are highly desired
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algorithms. Our research integrates expertise from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems
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of Engineering The new International Centre for Neuromorphic Systems, at The University of Manchester is hiring a Research Associate/Fellow for a two-year full-time role in Neuromorphic Systems (Algorithms). Ideal
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee We are looking for a Research Fellow to focus
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PhD Student (f/m/d) for the project Theory and Algorithms for Structure Determination from Single Molecule X-Ray Scattering Images Project description Single molecule X-ray scattering experiments with
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 15 days ago
, and approximation algorithms. The successful candidate will be expected to deliver a course similar to the outline presented here: https://www.utsc.utoronto.ca/~bretscher/c63/lectures.html
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statistical models to understand and explain biological phenomena. • Create algorithms to integrate large and diverse datasets into theoretical frameworks for modeling complex biological systems. • Collaborate