Sort by
Refine Your Search
-
Listed
-
Employer
- Harvard University
- Nature Careers
- Simons Foundation/Flatiron Institute
- Carnegie Mellon University
- Northeastern University
- Simons Foundation
- University of Michigan
- Boston College
- Genentech
- Lawrence Berkeley National Laboratory
- University of Maryland, Baltimore
- University of Michigan - Ann Arbor
- University of Texas at Austin
- AbbVie
- Dana-Farber Cancer Institute
- George Mason University
- Indiana University
- Oak Ridge National Laboratory
- Simons Foundation;
- Stanford University
- University of California
- University of Cincinnati
- University of North Carolina at Chapel Hill
- University of North Carolina at Charlotte
- 14 more »
- « less
-
Field
-
research team. Key research areas include: Development of low-carbon materials and tunable thermal energy storage materials integrated with smart sensors and advanced algorithms Creation of Digital Twins
-
challenge meeting this requirement is the simultaneous need for low-power consumption. The main objective of the project is to develop a complete end-to-end high-performance DNN system for on-premise
-
University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 15 hours ago
Duties and Responsibilities Responsibilities: 1. Conduct research on AI-driven methods, including reinforcement learning and diffusion models, for molecular and antibody design. 2. Develop algorithms, run
-
learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential tools. The successful applicant will be expected
-
computer science, statistics, operations research, or related computational fields. As part of an interdisciplinary research team dedicated to advancing management science, the fellows will develop novel
-
models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees. Research areas include Representation Learning, Machine learning and Optimization
-
progress in machine learning and artificial intelligence, the successful candidate will have primary responsibility to develop, implement, and test multimodal machine learning algorithms to analyze and
-
mitigation strategies. Validate, analyze, and interpret experimental data. Develop algorithms for near-term hardware based on critical evaluation of the literature, and original thinking. Design quantum
-
part of an interdisciplinary research team dedicated to advancing management science, the fellows will develop novel quantitative methods at the interface of statistical learning, experimental design
-
algorithm development, data analysis and inference, and image analysis Ability to do original and outstanding research in computational biology, and expertise in computational methods, data analysis, software