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candidate will work with Dr. Florence Bourgeois and Unit collaborators to develop an independent research project within the scope of the Center’s research program. In addition to carrying out data-driven and
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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pedagogy projects over the course of the year. The fellowship is renewable for a second year at the discretion of the Center. We plan to welcome three new and up to three returning fellows each year
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Qualifications Doctoral degree in statistics, biostatistics, computer science, applied mathematics, or a related quantitative field. Excellent programming skills, as well as strong oral communication and writing
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Qualifications PhD. required. Additional Qualifications Experience/interest in programming language, verification, artificial intelligence or machine learning. Individuals with a demonstrated track record in
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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the collection and analysis of child (preferably infant or toddler) data Strong written and oral communication skills Strong analysis and programming skills (preferably in R and/or python) Ability to work
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the collection and analysis of child (preferably infant or toddler) data Strong written and oral communication skills Strong analysis and programming skills (preferably in R and/or python) Ability to work
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datasets as well as optimally leveraging integration with existing genomics datasets. The role will often involve rapid prototyping in support of a dynamic, fast-moving experimental program; it is focused
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, epidemiology, biostatistics, data science, economics, pharmacy, medicine, or related fields Strong quantitative and programming skills, including proficiency in R, Python, or similar languages, and experience