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Functions Developing and implementing machine learning and deep learning models to analyze forestry, physiological, and ecological datasets Modeling plant growth, carbon allocation, stress response (e.g
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Engineering, Physics, or a similar field. Preferred Qualifications Strong technical background in one or more of the following areas: signal processing, advanced data analysis, statistics, and machine learning
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to detail. Ability to manage multiple projects independently and meet deadlines. Ability to collaborate effectively with researchers, staff, and peers. Ability to work in an office setting at a computer for
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in the following areas: Deep Learning, Scientific Machine Learning, Stochastjc Gradiant Descent Method, and Numerical PDE’s - Advised by Dr. Yanzhao Cao Probabilistic Graph Theory (Network Traversal
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Alabama weather conditions; demonstrated technical excellence; ability to work both independently and in a team environment. Minimum Technology Skills Proficiency in computer applications (Excel, PowerPoint
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: signal processing, advanced data analysis, statistics, and machine learning – Experience in safe laboratory procedures. Effective verbal and written communication skills. Laboratory experience
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are seeking applications from individuals with a PhD in any one area of engineering such as: aerospace, chemical, civil and environmental, computer science and software, electrical and computer, industrial and