Sort by
Refine Your Search
-
Listed
-
Employer
- Northeastern University
- National Aeronautics and Space Administration (NASA)
- Pennsylvania State University
- Cornell University
- George Washington University
- Rutgers University
- Stanford University
- University of Washington
- New York University
- University of North Carolina at Chapel Hill
- Argonne
- Indiana University
- South Dakota Mines
- University of California Irvine
- University of Florida
- University of Texas at Arlington
- University of Texas at Dallas
- University of Utah
- Yale University
- Boston University
- Brookhaven National Laboratory
- California Institute of Technology
- Lawrence Berkeley National Laboratory
- Massachusetts Institute of Technology
- SUNY University at Buffalo
- Sandia National Laboratories
- The University of Arizona
- Tufts University
- University of Arkansas
- University of Central Florida
- University of Colorado
- University of Illinois at Chicago
- University of Minnesota
- University of Pittsburgh
- Villanova University
- Virginia Tech
- Washington State University
- 27 more »
- « less
-
Field
-
: Strong skills in developing biosignal processing algorithms and implementing machine learning models for data interpretation. Technical Oversight: Ability to monitor complex data collection processes and
-
help develop new computational models that integrate molecular reaction networks with AI/ML algorithms in order to predict patient-specific cardiac remodeling and heart disease outcomes across human
-
the molecular biology of aging and neurodegenerative diseases. Engage in the development and testing/validation of new algorithms and their applications to transcriptomic, epigenomic, genetic, and proteomic data
-
quantitative modeling techniques and artificial intelligence methodologies in brain diseases. The candidate will work on developing advanced new algorithms, testing and validation, and applications in these data
-
will include development of algorithms for heterogeneous computing architectures and implementation of AI/ML in a real-time environment. The candidate will also have the opportunity to conduct
-
and human-based leadership. As organizations increasingly blend algorithmic and human decision-making, fundamental questions arise about how leadership operates, adapts, and creates value in this new
-
. Developing the algorithms, infrastructure, and governance necessary for such analysis can simultaneously enhance hypothesis generation, computational modeling, and post hoc support for laboratory studies and
-
expected to actively contribute to the project, work collaboratively as part of the research team, and perform the following major tasks: Conduct theoretical analysis, algorithm development, and simulation
-
; developing novel ways to combine quantum chemical methods and machine learning; developing quantum algorithms for computational chemistry on quantum computers; and applying existing and new computational
-
; developing novel ways to combine quantum chemical methods and machine learning; developing quantum algorithms for computational chemistry on quantum computers; and applying existing and new computational