Sort by
Refine Your Search
-
Listed
-
Employer
- Stanford University
- University of Washington
- Argonne
- National Aeronautics and Space Administration (NASA)
- New York University
- Northeastern University
- University of Florida
- Broad Institute of MIT and Harvard
- California Institute of Technology
- Carnegie Mellon University
- Cornell University
- Dartmouth College
- Georgia Institute of Technology
- Los Alamos National Laboratory
- Michigan Technological University
- Nature Careers
- Northwestern University
- Ohio University
- Princeton University
- University of Illinois at Chicago
- University of Maryland, Baltimore
- University of Massachusetts Medical School
- University of Southern California
- University of Texas at Arlington
- Zintellect
- 15 more »
- « less
-
Field
-
. PyTorch). Experience analyzing high-dimensional data (biological or otherwise) or single-cell, bulk sequencing, or other biological data. Experience in algorithms and good software development practices
-
National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 2 hours ago
: Technology Development Advisors: Ryan Rogalin Ryan.Rogalin@jpl.nasa.gov (818) 354-3426 Applications with citizens from Designated Countries will not be accepted at this time, unless they are Legal Permanent
-
frameworks (e.g. PyTorch). Experience analyzing single-cell, bulk sequencing, or other biological data. Experience in algorithms and good software development practices. Good communication skills. About the
-
by working to develop novel algorithms on finite element method, isogeometric analysis, geometric modeling, machine learning and digital twins to study various applications such as computational
-
/or observationally motivated model-building for SMBH feeding and feedback. The group integrates observations, theory, data analysis, algorithm development, model-building, and numerical simulations
-
, engineers, and researchers in an effort to develop medical automation research solutions. You will support various engineering and computer science aspects of research projects focused on optimizing combat
-
. university groups within CMS. Our instrumentation expertise spans detector operations and upgrades (Level‑1 muon trigger, CSC muon system), tracking algorithm R&D, and future HL‑LHC trigger algorithm
-
development. • Genotype-Phenotype Correlations in 9p-Related Syndromes: Investigating the genotype-phenotype correlations in 9p-related syndromes (e.g., 9p deletion syndrome, 9p duplication syndrome
-
project is to develop scalable and privacy-preserving Bayesian computational algorithms. The position is intended for two to three years, with an initial one-year appointment renewable contingent upon
-
postdoctoral scholars, working on the development of a core, scalable methodology. This methodology leverages existing spatial data on landscapes, fire behavior, and fuel treatments to evaluate real-world