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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 4 hours ago
optimization algorithms Extensive communications protocol design Solid understanding of physical/link layer communications, including synchronization, beamforming, and autonomous rate adaptation Point of Contact
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and automated fault detection and diagnosis (AFDD) algorithms to buildings Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork
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networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis
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Institut des Hautes Etudes Scientifiques | Bures sur Yvette, le de France | France | about 13 hours ago
applications of candidates from a wide range of backgrounds from theoretical physics to pure mathematics. Candidates with experience in tensor network algorithms, rigorous statistical mechanics, probabilistic
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computed tomography (CT) reconstruction, including sparse-view and limited-angle algorithms, and the application of advanced machine learning (ML) and computational imaging methods to scientific and
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/tools or machine learning algorithms. Good computer programming skills in R/Matlab/PerlPython. Knowledge of basic molecular biology, genomics, and epigenetics. Experience in next-generation sequencing
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classical computing algorithms are NP-hard or, in general, difficult to implement. Within your application, please provide a research proposal (no more than five pages) answering the following questions: What
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and embedded cryptography, and quantum programming languages. The section is part of the Department of Mathematics and Computer Science, and other research sections at the department are Algorithms
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developments, algorithmic implementation, and analysis. Experience with electronic structure and dynamics, non-adiabatic molecular dynamics, and coding is strongly selected for. Please seehttps
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on are: • approximation algorithms in QIT (e.g. ground state energies); • symmetry- and size reduction of polynomial optimization problems; • characterization of quantum codes and quantum capacities