Sort by
Refine Your Search
-
Listed
-
Employer
- Princeton University
- The University of Arizona
- University of Kansas Medical Center
- Wayne State University
- Harvard University
- Indiana University
- Nature Careers
- Oak Ridge National Laboratory
- Purdue University
- Rutgers University
- Stanford University
- University of Arkansas
- University of Central Florida
- University of Minnesota
- University of North Carolina at Chapel Hill
- University of Virginia
- Virginia Tech
- Yale University
- 8 more »
- « less
-
Field
-
learning, small data learning · Active learning, Bayesian deep learning, uncertainty quantification · Graph neural networks This position involves active participation in a well-funded
-
University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 10 hours ago
knowledge graphs. Your work will support the creation of FAIR-aligned metadata (including emerging standards like Croissant) to ensure data provenance, accessibility, and reuse across translational science
-
projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
-
, computational fluid dynamics and material science, dynamical systems, numerical analysis, stochastic problems and stochastic analysis, graph theory and applications, mathematical biology, financial mathematics
-
graph theory. Qualifications Candidates with a Ph.D. in any area of cognitive neuroscience broadly defined (e.g., Psychology, Neuroscience, Computer Science, or a related field) are welcome to apply
-
the theory of quantum graph states. Additional expertise in computational methods would be useful but is not necessary. The Postdoctoral and Senior Research Associate positions will also involve
-
publications and presentations. Collect, analyze and graph data, conclude research projects in a timely manner, write reports, and manuscripts. Engage in career development activities, apply for dedicated
-
of sparse matrix, tensor and graph algorithms on distributed and heterogenouscomputational environments. Basic Qualifications: A PhD in Computer Science, Applied Mathematics, Computational Science, or related
-
analysis of data. Prepares appropriate and understandable representations of data such as graphs, charts, tables, statistical summaries, etc. Contributes to the preparation of scientific manuscripts by
-
Responsibilities Research: - Conduct research in AI reasoning, semantic modeling, and knowledge graph development. - Develop and optimize graph databases for structured knowledge representation. - Apply neural