Sort by
Refine Your Search
-
Listed
-
Employer
- Argonne
- Nature Careers
- Stony Brook University
- University of North Carolina at Chapel Hill
- Duke University
- Stanford University
- Brookhaven National Laboratory
- Cornell University
- The University of Iowa
- University of California Berkeley
- Carnegie Mellon University
- New York University
- Northeastern University
- Rutgers University
- South Dakota Mines
- University of Colorado
- University of Miami
- University of Minnesota
- University of Washington
- Brown University
- Harvard University
- Purdue University
- SUNY University at Buffalo
- Sandia National Laboratories
- Texas A&M University
- The Ohio State University
- The University of North Carolina at Chapel Hill
- Tufts University
- University of California, Berkeley
- University of Nebraska Medical Center
- University of Nevada Las Vegas
- University of Texas at Arlington
- University of Utah
- 23 more »
- « less
-
Field
-
learning, and AI applications in radiology. The research area includes innovative work on developing Deep Learning Based Image reconstruction in CT on Photon Counting Detector CT with work in collaboration
-
-generation AI models of gene regulation and disease progression. Our work is redefining Parkinson’s disease biology and enabling translational breakthroughs. The role Develop deep learning models across genome
-
diseases, Genome Biology, 2024 S. Hudaiberdiev et al., Modeling islet enhancers using deep learning identifies candidate causal variants at loci associated with T2D and glycemic traits, PNAS, 2023 S. Li et
-
. Candidates with experience in dimension reduction, deep learning, machine learning, modeling neuroimaging data are especially encouraged to apply. Excellent written and communication skills are required
-
discipline Strong experience in integrating several of the following components: Deep learning and LLMs for molecular biology Vision foundation models for pathological image analysis Multi-omics datasets (e.g
-
modulation, radar/sonar signal processing, and machine and deep learning. WORK PERFORMING: Individual will perform research generally in the area of statistical signal and array processing. Topics of specific
-
in Utah to recruit multiple postdoctoral fellows to apply high throughput methods and machine/deep learning to unlock the full potential of the dark proteome. Responsibilities Scientific visionRibosome
-
partners, or translational research teams. Experience with Quarto, Python, and/or other programming languages. Experience and interest in data science or informatics education. Experience with deep learning
-
(but are not limited to) Computer Science, statistics, mathematics, automation, informatics, and Engineering. Experience in deep learning, machine learning and medical imaging processing Programming
-
integrates neuroimaging, sleep measurement, digital phenotyping, electronic health record (EHR) data, and deep clinical phenotyping to identify predictors of symptom trajectories and functional outcomes in