Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Stony Brook University
- European Space Agency
- Oak Ridge National Laboratory
- AALTO UNIVERSITY
- Bucharest Universty of Economic Studies
- CNRS
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Argonne
- KINGS COLLEGE LONDON
- Technical University of Munich
- The University of Arizona
- University of Luxembourg
- Aarhus University
- Aix-Marseille Université
- Brookhaven Lab
- Brookhaven National Laboratory
- CISPA Helmholtz Center for Information Security
- Caltech
- Delft University of Technology (TU Delft); yesterday published
- ETH Zürich
- Ecole Centrale de Lyon
- IRTA
- King's College London
- Lawrence Berkeley National Laboratory
- Linköpings University
- Luleå University of Technology
- Nantes Université
- National Aeronautics and Space Administration (NASA)
- Northeastern University
- Texas A&M University
- The University of North Carolina at Chapel Hill
- Télécom Paris
- UNIVERSITY OF VIENNA
- Universitatea Maritimă din Constanța
- University of Amsterdam (UvA)
- University of Amsterdam (UvA); today published
- University of California
- University of North Carolina at Chapel Hill
- University of Oulu
- University of Southern Denmark
- University of Trás-os-Montes and Alto Douro
- University of Turku
- University of Utah
- University of Washington
- Université Grenoble Alpes
- Wageningen University & Research
- Washington University in St. Louis
- Yale University
- 38 more »
- « less
-
Field
-
oral communication with a record of leading and reporting results. Desired Qualifications: Knowledge of quantum computing algorithms. Familiarity with tensor network methods. Experience programming GPUs
-
for the concept of optimal transport for inverse problems. Optimal transport is concerned with the mathematical problem of comparing and interpolating distributions of mass, for example probability distributions
-
increasing environmental awareness. However, most existing hearing aid algorithms optimize for only one of these objectives at a time, often at the expense of the others. To enhance hearing aid performance
-
demonstrated ability to work within a geographically distributed networks of collaboration Proven experience in developing and implementing machine learning models and algorithms, ideally in the healthcare
-
demonstrated ability to work within a geographically distributed networks of collaboration Proven experience in developing and implementing machine learning models and algorithms, ideally in the healthcare
-
University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 8 hours ago
and generative models. Develop novel algorithms for generative modeling tasks and optimize LLM/GPT-like models on large datasets. Stay abreast of advancements in language modeling and generative AI
-
verticals, Unmanned Aerial Vehicles, Integrated Satellite-Space-Terrestrial Networks, Quantum Communications and Key Distribution, Spectrum Management and Coexistence, Tactile Internet, Earth Observation, and
-
resources while addressing workflow requirements for scientific applications. Validate distributed intelligence algorithms at scale on ORNL's computational resources, including the Frontier supercomputer
-
modeling techniques and artificial intelligence methodologies in brain diseases. The candidate will work on developing advanced new algorithms, testing and validation, and applications in these data
-
terms of research and education, covering all aspects of computer science, including artificial intelligence, machine learning, data sciences, algorithms, databases, cloud computing, software engineering