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Field
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. The successful applicant will use state of the art inference algorithms to design, use and share the findings of epidemiological models that integrate across large and diverse datasets including capture-mark
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programming (e.g., Python, MATLAB). Preferred Qualifications: Experience in resilience analysis for multi-agent systems. Familiarity with communication-constrained algorithm design. Prior work on communication
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data analysis programs. Work with lab members to design image analysis algorithms to fulfill the research goals. Publishes activities and findings. Analyzes complex microscopy and data problems and
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and children’s health, nutritional sciences, population health and the molecular genetics of human disease. Our research links the causes of common health problems to life’s landmark stages, treating
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women and children’s health, nutritional sciences, population health and the molecular genetics of human disease. Our research links the causes of common health problems to life’s landmark stages
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., Python, MATLAB). Preferred Qualifications: Experience in resilience analysis for multi-agent systems. Familiarity with communication-constrained algorithm design. Prior work on communication-efficient and
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foundational course is designed for first-year students across all engineering disciplines and focuses on cultivating problem-solving abilities, algorithmic thinking, and technical communication skills in a
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Implement and maintain bioinformatics workflows for sequence analysis and protein characterization Collaborate on algorithm development to improve protein generation accuracy and diversity Laboratory
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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& AI hardware or brain-inspired AI algorithm development, spatial analysis of multi-omics data. We are particularly interested in applicants with a demonstrated track record of translating discoveries