Sort by
Refine Your Search
-
Listed
-
Employer
- Harvard University
- Simons Foundation/Flatiron Institute
- Nature Careers
- Northeastern University
- Carnegie Mellon University
- University of Michigan
- Simons Foundation
- Genentech
- George Mason University
- Korea Institute for Advanced Study
- The University of Alabama
- University of Maryland, Baltimore
- University of Michigan - Ann Arbor
- University of Texas at Austin
- AbbVie
- Dana-Farber Cancer Institute
- Embry-Riddle Aeronautical University
- Florida Atlantic University
- Indiana University
- Johns Hopkins University
- Lawrence Berkeley National Laboratory
- Massachusetts Institute of Technology
- Oak Ridge National Laboratory
- The University of North Carolina at Chapel Hill
- University of Alabama, Tuscaloosa
- University of California
- University of Cincinnati
- University of Michigan - Flint
- University of North Carolina at Chapel Hill
- University of San Francisco
- Zintellect
- 21 more »
- « less
-
Field
-
to remove PFAS. To accomplish these goals, the candidate will participate in the development of AI/ML algorithms for the prediction of chemical properties, infrared and mass spectra, and ionization cross
-
multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and their dynamics. Conducting literature searches, manuscript preparation, and
-
implementation of algorithms to analyze the data and integrate with other data sets including clinical outcomes data. This person will also help with the generation of tools needed for manipulating and preparing
-
, focusing on applications within the healthcare, education, and environment sectors. Designs generative AI techniques and algorithms for data integration and computational models, with objectives to amplify
-
Medicine and Bioinformatics. The specific objectives of the project are to (i) deploy network analysis methods to genomic data (50%), and (ii) develop such algorithms including community detection algorithms
-
with applications to aerospace systems Designing, implementing, and testing control algorithms in simulation and hardware platforms Contributing to publications and reports; presenting research findings
-
and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
-
learning, and data science, focusing on applications within the healthcare, education, and environment sectors. Designs generative AI techniques and algorithms for data integration and computational models
-
science, with a particular focus on neuroscience applications. Designs AI techniques and algorithms for multimodal data fusion (e.g., MRI, EEG, cognitive and behavioral data, blood biomarkers, and
-
(CPS) for aquaculture, to sensors and platforms for maritime applications. The Postdoc’s primary task will be to lead the development of algorithm, software, and hardware to extend the current HAUCS