Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Nature Careers
- Technical University of Munich
- University of Oxford
- NEW YORK UNIVERSITY ABU DHABI
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Stanford University
- ;
- Argonne
- University of North Carolina at Chapel Hill
- Duke University
- Pennsylvania State University
- KINGS COLLEGE LONDON
- Princeton University
- Singapore Institute of Technology
- University of Miami
- University of Minnesota
- Yale University
- Brookhaven Lab
- Leibniz
- New York University
- U.S. Department of Energy (DOE)
- University of California Berkeley
- University of Central Florida
- Carnegie Mellon University
- Cornell University
- Heriot Watt University
- King's College London
- Northeastern University
- Technical University of Denmark
- Texas A&M University
- University of Florida
- University of London
- University of Minnesota Twin Cities
- University of Vienna
- University of Washington
- Aarhus University
- Cold Spring Harbor Laboratory
- King Abdullah University of Science and Technology
- New York University of Abu Dhabi
- Oak Ridge National Laboratory
- RIKEN
- Radboud University
- Rutgers University
- South Dakota Mines
- Stony Brook University
- The University of Iowa
- UNIVERSITY OF VIENNA
- University of British Columbia
- University of California
- University of California Irvine
- University of Houston Central Campus
- University of Lund
- University of Maryland, Baltimore
- University of Nevada, Reno
- University of North Texas at Dallas
- University of Oklahoma
- University of Southern Denmark
- University of Texas at Arlington
- Utrecht University
- Virginia Tech
- ; King's College London
- ; Xi'an Jiaotong - Liverpool University
- AALTO UNIVERSITY
- Aalborg University
- Academia Sinica
- CEA-Saclay
- California State University, Northridge
- Canadian Association for Neuroscience
- Case Western Reserve University
- Chalmers University of Technology
- Copenhagen Business School , CBS
- Emory University
- Empa
- European Space Agency
- Forschungszentrum Jülich
- Genentech
- Georgia State University
- Ghent University
- Imperial College London
- Institut Pasteur
- Johns Hopkins University
- Los Alamos National Laboratory
- Manchester Metropolitan University
- National Aeronautics and Space Administration (NASA)
- National University of Singapore
- New York University in Abu Dhabi
- Purdue University
- Royal College of Art
- SUNY Polytechnic Institute
- SciLifeLab
- Sun Yat-Sen University
- Swedish University of Agricultural Sciences
- Syracuse University
- The Ohio State University
- The University of Arizona
- The University of Chicago
- Tsinghua University
- UNIVERSITY OF HELSINKI
- University College Cork
- University of California, Merced
- 90 more »
- « less
-
Field
-
cutting-edge big/deep data analysis methods, including machine learning and artificial intelligence. The ideal candidate will therefore have a strong background in data science and in the application and
-
NASA. The researcher will utilize multi-decadal satellite imagery and deep learning techniques to analyze temporal trends in urban structure and their impacts on microclimate, focusing on extreme heat
-
communication) Willingness to learn and confront new challenges Preferred Qualifications Doctoral research conducted in the area of machine learning for healthcare and related topics Deep knowledge of multi-modal
-
architectures, including terrestrial and non-terrestrial networks Deep learning for wireless communication problems, particularly in areas such as spectrum management, adaptive system design, or cognitive radio
-
learning, deep learning, and large language models (LLMs), for the analysis of high-throughput multi-omics datasets (especially single-cell and spatial omics) and large textual corpora (e.g., scientific
-
successful candidate will possess skills in natural language processing and deep learning. Experience of studying the robustness and generalisability of LLM would be beneficial. This is a full time post (35
-
CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
metabolomics data from clinical studies. Apply deep learning models (e.g., autoencoders, variational autoencoders, graph neural networks) for biomarker discovery, disease classification, and patient
-
U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 17 hours ago
receive hands-on experience that provides an understanding of the mission, operations, and culture of the DOE. As a result, fellows will gain deep insight into the federal government's role in the creation
-
ethical frameworks. Proficiency in Python and experience with relevant libraries for AI/ML development. Experience with advanced AI methodologies including deep learning, transfer learning, and neural
-
interpretable deep neural networks is required. Candidate must have published in top journal and conference at least one scientific paper in interpretable machine learning (not explanations of black boxes) among