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. Emphasis is placed on artificial intelligence/machine learning approaches applied to digital data and multi-omics data. Additional responsibilities include mentoring students, collaborating with faculty
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new insights into the phenomena observed and enrich the databases required for deep learning methods. The neural networks currently being developed at LISTIC to detect and segment areas of movement in
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the tissue. Analyzing research data using different computer software Generation of preliminary data for grant applications. Writing drafts of manuscripts. Coordinating with other investigators for lab
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in Machine Learning, Computer Science, Electrical Engineering, Geophysics, Applied Mathematics, or a closely related field. Demonstrated strong research skills, evidenced by high-quality publications
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and enthusiastic individual who meets the following criteria: Recently earned a Ph.D. in bioinformatics, computational biology, computer science, electrical and computer engineering, or a related
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-oriented Preferred Qualifications Proficiency in molecular biology techniques and directed evolution Experience with mechanistic modeling and/or machine learning/artificial intelligence to guide protein or
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for autonomous vehicle control and teleoperation applications. Expertise in the areas of vehicle dynamics, vehicle control, localization, computer vision, sensor fusion and estimation algorithms is desired
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fellows will receive joint mentorship from leading experts in metabolic biology, AI and machine learning, drug delivery, and translational medicine, while maintaining full academic independence in research
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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning
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Research Associate will contribute to developing and/or applying artificial intelligence, machine learning, and image segmentation and/or data science-based methods to address cutting-edge topics, including