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: Collaborate and participate in large consortia to assess needs and requirements Design and develop machine learning models for genomics applications Maintain and update existing deep learning frameworks
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environment where machine learning meets real-world scientific impact. What You’ll Do: Conduct cutting-edge research at the intersection of AI and science Develop large-scale deep learning models for scientific
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intelligence models for the analysis of multispectral remote sensing imagery. The main tasks include implementing computer vision and machine learning methods for the detection and prediction of algal blooms in
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Transformers). Analysis of existing datasets. Evaluation of the trained models on suitable datasets. What you contribute Good knowledge in the field of machine learning and training neural networks. Good Python
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Machine Learning - Developing Oral and written communications - Developing Programming Languages - Developing The core technical skills listed are most essential; additional technical skills may be required
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, designing, implementing, and evaluating ML models that address practical challenges across domains. The researcher will contribute to the development of a full machine learning pipeline, including data
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 12 hours ago
. Experience with technical software such in the fields of design, construction and/or building operations. Including programs such as: Dropbox, Microsoft Office Suite, 3D Modeling, and willingness to learn new
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models, and ensuring students have a structured and engaging learning experience. Career Readiness Competencies: Access & Opportunity Leadership Professionalism Essential Functions Teach assigned courses
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Computer Engineering. Expertise in computer vision algorithms and image processing techniques (such as object detection, segmentation, and feature extraction). Proficiency in deep learning frameworks such as
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systems, and/or human brain. Use of artificial intelligence and machine learning approaches is a plus. Details of current faculty and research in the Department of Anatomy & Neurobiology can be found