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machine learning and computer vision algorithms • Build tools for photogrammetric 3D reconstruction and defect detection • Evaluate and refine AI models using annotated data and real-world image datasets
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Working with cutting-edge methodologies in geostatistics and machine learning, you will analyse a rich data set recording the frequencies of genetic mutations that confer insecticide resistance in wild
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policies pertaining to other schools at Duke University. The postdoc candidate is expected to: 1) Develop novel methods for incorporating scientific machine learning in solving problems in solid mechanics
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Internal Number: 6483018 Assistant/Associate/Full Project Scientist - Machine Learning & Data Analytics Advanced Bioimaging Center Department of Molecular and Cell Biology Position overview Position title
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models for large scale quantitative, image, and text information systems. The machine learning and information retrieval includes methodologies such as Boolean, vector space, probabilistic, inference net
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to above shoulders up to 25 pounds. Standing and sitting at computer terminals and laboratory bench completing repetitive tasks for extensive periods of time. Shift Normal shift is 8 hours during weekdays
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) Medicine. You have knowledge in the fields related to anatomy and clinical procedures. You are acquainted with computer programmes related to making virtual reality models. You enjoy finetuning the details
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an admissions representative role. Strong communication and listening skills. Computer skills including experience using customer relationship management systems and the ability to learn new systems quickly
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and reporting tools (e.g., Tableau, Power BI) Natural Language Processing (NLP) or machine learning techniques Knowledge of version control systems (e.g., Git) Required Documents Resume Cover Letter
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Status Reports to the Principal Investigator (Dr. Leluo Guan). Will work with Post-Doctoral Fellows to establish omics data storage, transfer and management, and develop machine learning models