Sort by
Refine Your Search
-
Employer
- Cornell University
- University of North Carolina at Chapel Hill
- University of Washington
- University of Maryland, Baltimore
- Duke University
- New York University
- Rutgers University
- Northeastern University
- Stanford University
- Stony Brook University
- University of New Hampshire
- University of Texas at Arlington
- University of Texas at Dallas
- Yale University
- Boston University
- Lehigh University
- Texas A&M AgriLife
- Texas A&M University
- University of Alabama at Birmingham
- University of Arkansas
- University of Illinois at Chicago
- University of Massachusetts Chan Medical School
- University of North Texas at Dallas
- University of Utah
- University of Virginia
- Virginia Tech
- Washington State University
- 17 more »
- « less
-
Field
-
(NLP) algorithms applied to electronic health records (EHR) to understand cannabis-related harms in aging PWH and people without HIV. The position will entail collaborations with several investigators
-
simulations and data analysis. This includes data analysis using Python-based algorithms. Experience with EELS is preferred. Skills This See Experience
-
languages like Python or C, and or developing and/or using computational methods for analyzing large datasets. Demonstrated experience in developing computational algorithms for solving problems, preferably
-
University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
world. Position Summary The postdoctoral researcher will conduct advanced research in artificial intelligence (AI) and machine learning, with a focus on developing novel algorithms and systems. The position offers
-
experience in simulating/implementing quantum algorithms for field theories on quantum hardware. Appointment Detail: This post‑doctoral position is a full‑time, 12‑month appointment with annual renewal
-
importance in quantum materials research. While practical quantum applications typically require stable quantum bits with long coherence times, this research proposes innovative programmable algorithms
-
will contribute to high-impact projects, including: 1. Developing and validating algorithms that extract data from the Epic EHR (e.g., large language models) via comparison with manually extracted data
-
typically require stable quantum bits with long coherence times, this research proposes innovative programmable algorithms that can harness the power of imperfect quantum simulators to tackle complex
-
testing of model-free algorithms for real-time optimization of turbine operating conditions (e.g., yaw set points). Other projects may be assigned by the supervisor depending on skills and technical needs
-
) and genetics data which are measured by longitudinally and cross-sectionally. • Developing and applying machine learning and AI approaches to identify interactive topological relationships