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Field
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grid analytics, and scientific imaging. The successful candidate will design and implement sparse algorithms for large-scale scientific and numerical computations. This role offers an exceptional
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machine learning algorithms for application to sonar and underwater acoustics, as well as the accompanying data analysis to effectively characterize their performance in the Advanced Technology Laboratory
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master’s degree in related fields (computer science, electrical engineering, or computer engineering) Previous experience in Python programming Experience implementing machine learning algorithms in python
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. The ideal candidate will: (i) have a strong quantitative background; (ii) have significant experience with coding and computing; (iii) be able to work independently to solve problems; and (iv) have a long
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/Statistics, Medical/Health Informatics. Strong computational and programming skills with abilities to develop cutting-edge large-scale machine/deep learning algorithms using high-performance computing (HPC
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settings. Develop and test algorithms for object detection, tracking, and classification using LiDAR sensors. Help guide and mentor graduate students and other junior team members working on the project
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Development of imaging and sensing systems for data collection Support the implementation of various algorithms for computation at the edge Design experiments for parameter space exploration Publish research in
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 10 days ago
computationally intensive, relying on iterative time-marching algorithms to reconstruct heating environments. This limits their use in more advanced computational analyses, such as uncertainty quantification
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. Interest in clinical algorithm development and dexterity with biostatistical coding in R or Python is a plus. The primary goal of this aspect of the CH CARE Study is to combine serially obtained somatic and
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. Responsibilities* Design, implement, and evaluate LiDAR-based experiments in lab and real-world settings. Develop and test algorithms for object detection, tracking, and classification using LiDAR sensors. Help