University of California - Los Angeles (UCLA)
Staff Research Associate 3
University of California - Los Angeles (UCLA), Los Angeles, California, United States, 90079
Overview
The University of California Los Angeles (UCLA) is seeking a highly motivated and creative machine learning scientist with expertise in image segmentation. The selected candidate will work with the PI to implement and parameterize a computer vision deep learning model to classify giant kelp canopy from high resolution satellite imagery. Responsibilities
Develop, train, and evaluate computer vision deep learning models for image segmentation of giant kelp canopy in high resolution satellite imagery. Collaborate with the principal investigator to parameterize models and validate results on representative datasets. Preprocess and manage imagery data, assess data quality, and implement reproducible workflows. Summarize findings and communicate results to multidisciplinary teams. Qualifications
Experience with machine learning and image segmentation; strong background in computer vision and deep learning. Proficiency in programming languages and frameworks commonly used in ML (e.g., Python, TensorFlow/PyTorch). Ability to work collaboratively with researchers and present results clearly.
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The University of California Los Angeles (UCLA) is seeking a highly motivated and creative machine learning scientist with expertise in image segmentation. The selected candidate will work with the PI to implement and parameterize a computer vision deep learning model to classify giant kelp canopy from high resolution satellite imagery. Responsibilities
Develop, train, and evaluate computer vision deep learning models for image segmentation of giant kelp canopy in high resolution satellite imagery. Collaborate with the principal investigator to parameterize models and validate results on representative datasets. Preprocess and manage imagery data, assess data quality, and implement reproducible workflows. Summarize findings and communicate results to multidisciplinary teams. Qualifications
Experience with machine learning and image segmentation; strong background in computer vision and deep learning. Proficiency in programming languages and frameworks commonly used in ML (e.g., Python, TensorFlow/PyTorch). Ability to work collaboratively with researchers and present results clearly.
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