Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Brookhaven Lab
- Stanford University
- University of North Carolina at Chapel Hill
- Argonne
- Loyola University
- New York University
- University of South Carolina
- Carnegie Mellon University
- Duke University
- Medical College of Wisconsin
- Oak Ridge National Laboratory
- Princeton University
- Stony Brook University
- University of Miami
- University of Minnesota
- University of Washington
- Yale University
- Brookhaven National Laboratory
- Michigan Technological University
- Rutgers University
- Texas A&M University
- University of Florida
- University of Nevada Las Vegas
- Case Western Reserve University
- Central State University
- Cornell University
- Harvard University
- Indiana university Indianapolis
- LIGO Laboratory
- Los Alamos National Laboratory
- Nature Careers
- North Carolina A&T State University
- Pennsylvania State University
- Texas A&M AgriLife
- Texas A&m Engineering
- The University of Arizona
- The University of Chicago
- U.S. Department of Energy (DOE)
- University of Central Florida
- University of Colorado
- University of Maryland, Baltimore
- University of Michigan
- University of Nebraska Medical Center
- University of Oklahoma
- University of Oregon
- University of Southern California
- University of Texas Southwestern Medical Center
- University of Texas at Arlington
- University of Texas at Dallas
- 39 more »
- « less
-
Field
-
will work on multiple projects funded by NIH/NHGRI. The objective of the position is to develop novel statistical methods and computer software and analyze large scale biological data from biobanks
-
. The appointee will primarily conduct research applying advanced machine learning/AI (including techniques like deep learning) to analyze complex biological and clinical data (e.g., single-cell multi-omics
-
data from both tissue and single cells, for improved understanding of Alzheimer progression. Experience in brain disorders, machine learning and deep learning will be a plus. Interested candidates should
-
. The processes involved in triggering outbursts, using optical monitoring and the real-time pipeline X-ray Binary New Early Warning System (XB-NEWS) developed at NYUAD, and comparisons to AGN and other compact
-
d) excellent written, oral communication skills e) strong data analysis skills. Ideal applicants will also have experience with some combination of: a) Machine learning e) code optimization and
-
the pre- and post-processing of Magnetic Resonance (MR) images (or utilization of existing brain imaging markers), taking peripheral or central biomarkers, and regressing them against those images using
-
expertise in respiratory physiology and pertinent cellular and/or molecular mechanisms. Technical expertise in computer programming languages including R, Phython, and LabView are welcomed. Demonstrated
-
4D flow imaging, proficiency in machine learning applications relevant to neuroimaging, familiarity with fluid dynamics and its application to physiological data, and ultrasound imaging is desired
-
longitudinal modeling, machine learning methods, subgroup analysis, or other advanced modeling techniques is highly desirable. Software Proficiency: Experience with neuroimaging tools such as AFNI, SPM, FSL
-
relevant field at the PhD level with zero to five years of employment experience. Experience with deep learning frameworks (PyTorch, TensorFlow, JAX). Strong background in computational image processing and