Sort by
Refine Your Search
-
analysis using the Digital Signal Processing (DSP) toolbox in MATLAB (including novel analyses), and data visualization via YAEL (Your Advanced Electrode Localizer). The successful candidate will also have
-
research areas include Biomedical applications, Communication systems and information theory, Digital systems and computer architecture, Microelectronics, Micro-electromechanical systems (MEMS), Nano
-
related field. The ideal candidates will have experience in one or more of the following topics: deep learning for image and point cloud data processing, deep learning for time series data prediction
-
: Performs specialized research techniques and procedures related to phenotypic characterization of cardiovascular disease using available signal-based and imaging techniques. Compiles and analyzes data using
-
, electrical engineering, experimental physics, or a related field Strong programming and signal processing skills, with experience in Python and/or MATLAB Demonstrated ability to work independently and
-
National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 14 hours ago
. Collaborating with CA-SSN’s diverse ecosystems will provide invaluable input to NASA’s data development process, ensuring that data products are broad enough to support a range of questions while also being
-
by application materials. Doctoral coursework that included advanced statistics courses, as evidenced by application materials. Work history that required the uses of traditional and digital
-
processing. Proficiency in programming languages such as Python, MATLAB, or Java/Kotlin (for Android). Passion for innovation in digital health, fitness, and rehabilitation. Preferred Qualifications Background
-
point cloud data processing, deep learning for time series data prediction, digital twin, geospatial mapping with vehicle and UAV mounted remote sensing systems or robotic systems, crowd simulation