Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Stony Brook University
- Oak Ridge National Laboratory
- AALTO UNIVERSITY
- Bucharest Universty of Economic Studies
- European Space Agency
- Technical University of Munich
- Argonne
- KINGS COLLEGE LONDON
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- The University of Arizona
- The University of North Carolina at Chapel Hill
- Universitat Politècnica de Catalunya (UPC)- BarcelonaTECH
- University of Luxembourg
- University of Utah
- University of Washington
- Washington University in St. Louis
- XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU)
- ;
- Aarhus University
- Aix-Marseille Université
- Brookhaven Lab
- CISPA Helmholtz Center for Information Security
- CNRS
- Caltech
- Delft University of Technology (TU Delft); yesterday published
- Eindhoven University of Technology (TU/e)
- IRTA
- King's College London
- Lawrence Berkeley National Laboratory
- Linköping University
- Linköpings University
- Luleå University of Technology
- Lunds universitet
- National Aeronautics and Space Administration (NASA)
- Nature Careers
- Northeastern University
- Technical University of Denmark
- Texas A&M University
- The Cyprus Institute
- Télécom Paris
- UNIVERSITY OF VIENNA
- Universitatea Maritimă din Constanța
- University of Amsterdam (UvA)
- University of Amsterdam (UvA); today published
- University of California
- University of Oulu
- University of Southern Denmark
- Université Grenoble Alpes
- Xi'an Jiaotong - Liverpool University
- 39 more »
- « less
-
Field
-
learn a monolithic, “black-box” world model, often using a large neural network as function approximators. While these models can be highly effective for prediction within their training distribution
-
space)? What are appropriate descriptors of spatial distribution in the field of materials science (e.g., Voronoi tessellations, particle-particle distances, etc.)? What are appropriate algorithms
-
will have the opportunity to engage in pioneering research, collaborate with a large, dynamic and multidisciplinary team, and advance the field of quantum computing through innovative algorithms and
-
platforms. Our group develops advanced algorithms and data analysis methods to address fundamental scientific challenges, including global cloud distributions, cloud microphysical properties and processes
-
funding, Profs. Himanshu Gupta and CR Ramakrishnan conduct research in the general area of quantum networks, quantum sensor networks, and distributed quantum computing. The center includes other quantum
-
feedback. The research connects to international initiatives and offers opportunities to collaborate with leading European groups developing open and trustworthy AI systems at scale. Out-of-Distribution
-
collaborators. Your work will develop algorithms, inference methods, and frameworks to adapt models from training data to test environments, which is necessary to resolve distribution shifts, hidden confounders
-
is concerned with the mathematical problem of comparing and interpolating distributions of mass, for example probability distributions. The concept has lately gained increasing interest from
-
machine learning. Essential Duties and Responsibilities: Develop and implement advanced reconstruction algorithms for correlated and low-dose imaging modalities. Maintain and extend Python-based software
-
Postdoctoral Researcher position. Part-time 80 hours/month distributed unequally, gross hourly salary of 80 lei, fixed period until June 30, 2026. The project is entitled “A Study of Consumer Trust in Online