Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Michigan State University
- University of Arkansas
- NEW YORK UNIVERSITY ABU DHABI
- Simons Foundation
- University of British Columbia
- University of Oslo
- Carnegie Mellon University
- City of Hope
- Colorado State University
- Dana-Farber Cancer Institute (DFCI)
- Indiana University
- King Abdullah University of Science and Technology
- Nanyang Technological University
- New England HERC
- Northeastern University
- University of Copenhagen
- AITHYRA GmbH - Research Institute for Biomedical Artificial Intelligence of the Austrian Academy of Sciences
- Boise State University
- NYU Langone Health, Skok Lab
- National University of Singapore
- Sandia National Laboratories
- Simons Foundation/Flatiron Institute
- The University of Arizona
- UNIVERSITY OF NOTTINGHAM NINGBO CHINA
- UiT The Arctic University of Norway
- University of California, San Diego
- University of Delaware
- University of Idaho
- University of Michigan
- University of North Carolina at Chapel Hill
- University of South Carolina
- University of Texas Rio Grande Valley
- University of Texas at Austin
- 23 more »
- « less
-
Field
-
University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 11 hours ago
integrating mechanistic modeling and machine learning methods to analyze and predict drug properties, patient responses, and benefit-risk profiles, using real-world and regulatory datasets. This
-
• Develop and apply reduced-order modeling approaches using spatiotemporal decompositions of large high-resolution simulation datasets. • Develop and train machine learning architectures using reduced
-
learning-assisted methods: data assimilation, uncertainty quantification (UQ), and machine-learning-based moment closure models. · Multiscale modeling: kinetic limits of many-particle dynamical systems
-
conduct collaborative research at the intersection of non-canonical kinetic theory, non-conventional plasma turbulence modeling, high-speed flows, scientific machine learning for multi-physics problems
-
We are seeking creative and energetic candidates with strong experience in multimodal machine learning and human behavior analysis and modeling for a one-year Postdoctoral position. Using recent
-
We are seeking creative and energetic candidates with strong experience in multimodal machine learning and human behavior analysis and modeling for a one-year Postdoctoral position. Using recent
-
modeling Experience with machine learning, hydrologic modeling, or energy systems modeling (e.g., ParFlow, WEPPCloud, agent-based models) Proficiency in scientific programming languages (e.g., Python
-
engineering, mathematics, and statistics, are particularly encouraged to apply if they have experience in machine learning, systems modeling, optimization, or analysis of complex biological and clinical data
-
King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 14 hours ago
-assisted subsurface characterization and monitoring Distributed Acoustic Sensing (DAS) data processing and compression using ML Physics-driven machine learning for geophysical modeling and inversion
-
Instructions Application through http://jobbnorge.no : https://www.jobbnorge.no/en/available-jobs/job/302170/up-to-5-phd-fellows-in-machine-learning-at-the-arctic-institute-for-ai-in-science-and-innovation