Sort by
Refine Your Search
-
Listed
-
Employer
- Stony Brook University
- Oak Ridge National Laboratory
- Stanford University
- University of North Carolina at Chapel Hill
- George Washington University
- National Aeronautics and Space Administration (NASA)
- University of Central Florida
- University of Maryland, Baltimore
- Argonne
- Argonne National Laboratory
- Duke University
- Fred Hutchinson Cancer Center
- Indiana University
- Nature Careers
- Rutgers University
- Texas A&M AgriLife
- The University of North Carolina at Chapel Hill
- University of California
- University of Florida
- University of Texas at Arlington
- University of Washington
- 11 more »
- « less
-
Field
-
Requisition Id 16262 Overview: We are seeking a postdoctoral researcher to work at the intersection of tensor networks, quantum algorithms, scientific computing, topological physics, and quantum
-
unsupervised techniques, time-series modeling, and clustering algorithms. The candidate is expected to lead an effort to prepare generalized ML techniques for data quality monitoring for tasks across multiple
-
computational algorithm(s), perform data analysis, collaborate with biologists and physicians. He or she will lead multiple projects, work in a multidisciplinary environment and present/publish the results in
-
associate will work both independently and collaboratively to develop and apply novel deep learning algorithms and/or computational chemistry methods for small-molecule drug discovery targeting RNA
-
will have the opportunity to develop innovative algorithms and models that integrate multiple data modalities, collaborate with industry partners, and contribute to high-impact publications. Job
-
project integrates expertise across multiple levels—from circuits and architectures to algorithms, models, and systems—and includes opportunities for radiation testing at the NASA Space Radiation Laboratory
-
, Bioinformatics and Epidemiology (BBE) within VIDD at Fred Hutch in Seattle, WA. The group works on multiple projects investigating the immunological correlates of protection for novel tuberculosis vaccine
-
research. The ideal fellow will be interested in developing and applying novel computational algorithms to novel datasets generated in the setting of non-neoplastic and neoplastic disease. Key
-
) and Computational Fluid Dynamics (CFD), for polymer composite manufacturing processes Perform multi-physics simulations involving coupled thermal, mechanical, and material behavior across multiple
-
scholarly sector. AI3 includes more than 70 faculty members with interests ranging from novel algorithms, architectures, and mathematical / ethical foundations to applications in art, biological sciences