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decision-making for complex infrastructure systems. This position offers an opportunity to contribute to interdisciplinary research at the intersection of civil engineering, machine learning, and systems
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, with a focus on building multimodal AI models to predict dental caries progression. The successful candidate will work on developing deep learning and computer vision models using longitudinal dental
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learning outcomes and instructional practices. The position supports a collaborative research initiative led by faculty and staff from the College of Arts and Sciences and the College of Education and Human
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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to learn and lead exciting research projects that blend methods in pharmacoepidemiology with Artificial intelligence (AI)/Machine learning (ML) techniques to generate real-world evidence on the use
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pathways with the goal of developing novel therapies for cancer treatment. Learns and utilizes new techniques. Conceptualizes and executes complex laboratory experiments across a variety of fields from
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Writing for scholarly and applied audiences Delivering presentations to diverse stakeholders Preferred qualifications: Extensive knowledge of and experience with instructional technology and online learning
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data Write scientific manuscripts describing research findings Attend national and international meetings to present research findings, learn about the latest advances in the field, and develop a
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. The candidate will have the opportunity to learn and lead exciting research projects that blend methods in pharmacoepidemiology with Artificial intelligence (AI)/Machine learning (ML) techniques to generate real
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scientific manuscripts describing research findings Attend national and international meetings to present research findings, learn about the latest advances in the field, and develop a scientific network Apply