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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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academic research, scientific inquiry, and the pursuit of new knowledge in data science, or biomedical informatics. Strong programming skills and familiarity with deep learning platforms. Experience
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and provide relevant information to inform NIST management and stakeholders - Maintain deep technical knowledge of advances in the application of artificial intelligence and machine learning
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the field of frugal or green AI TECHNICAL SPHERE You have a proven experience in frugal, green or low-resource AI Strong grasp of deep learning architectures (CNN, RNN, Transformers, LLMs). Experience in fine
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advising, delivers group training, and contributes to outreach and partnership activities that advance the program’s impact across Virginia. This role requires deep knowledge of small business finance
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teams, manage complex programs, and inspire staff toward excellence. 3. Deep knowledge of evidence-based substance use treatment approaches and the unique needs of adult and student populations. 4. Proven
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Abilities: Federal Fluency: Deep operational and knowledge and federal contract negotiation experience under NSPM-33, NIST 800-171, and the FAR/DFARS. Working knowledge of export control regulations, Bayh
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employment contract, stay abreast of current negotiations and learn about collective bargaining at UC: https://ucnet.universityofcalifornia.edu/labor/bargaining-units/index.html High quality and low-cost
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contributions. Baylor has a comprehensive benefits plan that supports you and your family's wellbeing and allows you to be a part of the life of a vibrant and active college campus. To learn more, go to Baylor
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(pre-processing, filtering, feature extraction in the time, frequency, and time-frequency domains). Development and validation of machine learning and deep learning models; integration and analysis