Sort by
Refine Your Search
-
Listed
-
Employer
- University of North Carolina at Chapel Hill
- Argonne
- Oak Ridge National Laboratory
- University of Minnesota
- Stanford University
- University of California Berkeley
- Nature Careers
- SUNY Polytechnic Institute
- Duke University
- Stony Brook University
- University of Miami
- Wayne State University
- Carnegie Mellon University
- National Aeronautics and Space Administration (NASA)
- Pennsylvania State University
- Texas A&M University
- The Ohio State University
- U.S. Department of Energy (DOE)
- University of Washington
- Brookhaven National Laboratory
- Cornell University
- Indiana University
- Northeastern University
- South Dakota Mines
- University of Texas at Arlington
- Axoniverse
- Baylor College of Medicine
- Episteme
- Harvard University
- Johns Hopkins University
- Kennesaw State University
- Massachusetts Institute of Technology
- New York University
- Princeton University
- Purdue University
- Rutgers University
- SUNY University at Buffalo
- San Diego State University
- The Rockefeller University
- University of California, Berkeley
- University of Central Florida
- University of Colorado
- University of Florida
- University of Maine
- University of Maryland, Baltimore
- University of Nevada, Reno
- University of New Hampshire – Main Campus
- University of Texas at Tyler
- Virginia Tech
- Zintellect
- 40 more »
- « less
-
Field
-
National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 3 hours ago
. Description: This project aims to develop a next-generation wildfire risk assessment platform that tightly integrates Earth Observation (EO) data, deep learning, and dynamic fire behavior modeling
-
using deep learning, computational chemistry, medicinal chemistry, chemical biology, and molecular cell biology to develop novel therapeutics to tackle complex diseases such as cancers. Successful
-
University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 1 hour ago
inventories) with satellite remote sensing data (e.g., spaceborne lidar and/or hyperspectral observations) and apply machine learning and deep learning approaches to address these questions. This position is
-
Infrastructure Sciences Division. Machine learning (ML), specifically deep learning (DL), has been demonstrated to successfully predict the weather for 1-14 days with skill on par with numerical weather prediction
-
novel machine learning models—including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning—to fuse multimodal data from diverse experimental probes like Bragg
-
language processing), machine learning, or data science. Preferred Qualifications Expertise in Deep Learning and LLMs(Large Language Models): Knowledge in building applications and fine-tuning models like Llama 3
-
for candidates with a strong computer science background, such as algorithms, machine learning and data science. Key Responsibilities Develop, implement, and evaluate machine learning and deep learning models
-
Cultural Studies, History, or related field Demonstrated expertise with large language models (fine-tuning, prompting, deployment) Strong Python programming with deep learning frameworks (PyTorch, TensorFlow
-
and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning
-
in Ithaca, NY with a focus on developing deep learning algorithms. Dr. Haiyuan Yu, Ph.D. is a Tisch University Professor of Computational Biology in the College of Agriculture and Life Sciences and a