Sort by
Refine Your Search
-
Listed
-
Employer
- NIST
- University of Dayton
- Oak Ridge National Laboratory
- Princeton University
- Stony Brook University
- Carnegie Mellon University
- Texas A&M University System
- University of Houston Central Campus
- Zintellect
- California Institute of Technology
- Lawrence Berkeley National Laboratory
- Northeastern University
- Pennsylvania State University
- Purdue University
- Texas A&M AgriLife
- The Chinese University of Hong Kong
- The Ohio State University
- University of California, Los Angeles
- University of Illinois at Urbana Champaign
- University of Maryland
- University of Texas at Arlington
- University of Texas at Austin
- University of Texas at Tyler
- University of Virginia
- Washington State University
- 15 more »
- « less
-
Field
-
sensor data) mentioned. * Experience with multi-omics data analysis (e.g., genomics, transcriptomics, proteomics). * Familiarity with neuroimaging data analysis tools (e.g., FSL, SPM, or FreeSurfer
-
. clinical data, imaging data, genomic and omics data, device and sensor data) mentioned. ● Experience with multi-omics data analysis (e.g., genomics, transcriptomics, proteomics). ● Familiarity with
-
development on undersea sensor systems employed on Naval Special Warfare platforms. Responsibilities Communicate and collaborate with team members to design and develop new software features and maintain
-
of digital technologies for individuals with mental illness. These technologies may include algorithms, wearable sensors, and apps for digital phenotyping, ecologically valid assessment (e.g., cognition
-
, and collaborative remote sensing science. The research includes the following activities: • Developing and applying algorithms for analyzing imaging spectroscopy data from airborne and spaceborne
-
industrial automation, machine learning, mobile robotics, process control, sensor processing, machine vision, and/or human machine interaction. This position will require working with external partners
-
portfolio in AI4Science. The Computational Sciences Department at PPPL was formed to provide a focus for computational physics and engineering. We specialize in algorithms and applied mathematics, data
-
research in PPPL-relevant AI4Science topics. The Computational Sciences Department at PPPL was formed to provide a focus for computational physics and engineering. We specialize in algorithms and applied
-
languages; writing and testing logic in hardware description languages; developing and testing signal processing algorithms from concept to implementation; and performing systems integration and testing
-
and testing software in high level languages; writing and testing logic in hardware description languages; developing and testing signal processing algorithms from concept to implementation; and