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
- University of Michigan - Ann Arbor
- Genentech
- George Mason University
- Lawrence Berkeley National Laboratory
- University of California
- University of Maryland, Baltimore
- University of Texas at Austin
- AbbVie
- Boston College
- Dana-Farber Cancer Institute
- Florida Atlantic University
- Indiana University
- Oak Ridge National Laboratory
- Simons Foundation;
- Stanford University
- University of Cincinnati
- University of Michigan - Flint
- University of North Carolina at Chapel Hill
- Zintellect
- 16 more »
- « less
-
Field
-
opportunities exist at the intersection of mathematics, computer science, statistics, and their scientific applications, with the lines between theory, algorithm development and software implementation often
-
scalable quantum algorithm development and quantum-HPC codesign. What is Required: PhD in Computer Science, Computational Science, Applied Mathematics, or a related field awarded within the last five years
-
Research. We are seeking applications from researchers in the broad domain of computational and applied mathematics, including algorithm analysis, artificial intelligence, combinatorial scientific computing
-
mentor graduate students, contribute to grant proposal development, engage in agency outreach and partnership activities, publish high-quality research articles, and represent U-M at national professional
-
operational hydrologic modeling systems and decision-support tools for flood and drought risk management. The postdoc will also mentor graduate students, contribute to grant proposal development, engage in
-
scientists, biomedical informaticians, clinicians, and public health researchers to develop deployable, trustworthy methods that improve patient outcomes and health system operations. Key responsibilities
-
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
-
settings. Develop and test algorithms for object detection, tracking, and classification using LiDAR sensors. Help guide and mentor graduate students and other junior team members working on the project
-
. Responsibilities* Design, implement, and evaluate LiDAR-based experiments in lab and real-world settings. Develop and test algorithms for object detection, tracking, and classification using LiDAR sensors. Help
-
. Researching and developing novel machine learning architectures for integration across multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and