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Teaching/advising statement (describing the candidate’s teaching philosophy and practices as well as their approach to creating a learning environment in which students are encouraged to ask questions and
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. or equivalent degree in Machine Learning, Computer Science, Electrical Engineering, Geophysics, Applied Mathematics, or a closely related field. Demonstrated strong research skills, evidenced by high
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single synthetic program of computational geometry. Specific interests include morphology, design topology, discrete differential geometry, packings, and machine learning methods for unstructured geometric
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areas: Generative AI Agentic AI Graph Representation Learning and Modeling Foundation Models Large Language Models Multimodal Learning Basic Qualifications A Ph.D. or equivalent degree in Machine Learning
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of biomechanics and computer vision to document the wingbeat frequencies and phototactic behaviors of diverse insects under diverse contexts. Candidates will be expected to plan and lead behavioral experiments
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. Develop learning exercises, hands-on activities, workshops, and demos on various new and emerging topics such as AI, machine learning, embedded systems, and digital fabrication techniques. Collaborate and
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knowledge collections that have been stubbornly inaccessible, sometimes for centuries. Their understanding of machine learning and AI fundamentals will help identify areas of high impact and utilize models
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for extended periods of time and sitting using near vision for reading and computer use for extended periods of time. Working Conditions Work will be performed at a bench, in the tissue culture room, or at a
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Institute or working on machine learning, artificial intelligence, or computational neurobiology at Harvard. A research proposal of no more than 3 pages (1500 words, exclusive of references) outlining plans
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Application Type: Postdoctoral Location: Cambridge, Massachusetts 02138, United States of America Subject Area: Statistics / Machine Learning Appl Deadline: none (posted 2024/10/18) Description: Apply