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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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these plants. The post-doc is expected to build upon existing in-house tools and, where applicable, enhance them by means of AI (machine learning) and data-driven methods. These models are aimed to support
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design, computational fluid dynamic modelling, and assessment of thermo-fluid systems for aviation, focusing on icing in aircraft fuel systems. About You You will be educated to doctoral level in a
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model or machine-learning-enabled assets at a company or University). Basic understanding of early-stage technology development. Knowledge of basic principles of intellectual property and licensing
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use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and
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to significantly extend our existing team’s capabilities for data scoring and analysis (e.g., with expertise in natural language processing, machine learning, or computational modeling). Finally, the
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scientists, and machine learning experts will be an essential and enriching component of the position. Strong candidates will have a background in machine learning and natural language processing (NLP), with a
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to participate in building machine learning models, co-author publications, and contribute to grant proposals. Tentative start date: January 2024 for the Spring 2024 semester with possibilities of renewal
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assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu Employment Requirements Any offer of employment
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learning spaces while modeling healthy lifestyle practices. What You’ll Do: Teach fitness classes using safe, effective, and appropriate methods tailored to participant skill levels. Plan and deliver