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DNA elements and transcriptional and chromatin remodeling machinery in gene regulation. More information about the lab and specific research areas can be found at https://adelman.hms.harvard.edu
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). Additional Qualifications A strong research record demonstrated by publications in leading peer-reviewed journals and conferences (e.g., NeurIPS, ICML, ICLR, Neuron, Nature Methods, or related venues) is
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computational efforts across multiple labs at Harvard’s Faculty of Arts and Sciences and Medical School. As part of this effort, the Rubin lab is implementing new methods of studying aging in vitro using brain
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related quantitative field for a one-year Postdoctoral Research Fellow position. This position involves developing new theory and methods at the intersection of causal inference and network science
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Postdoctoral Fellow with Professor Morgane Austern. Professor Austern’s group focuses on research in high-dimensional statistics, probability theory, machine learning theory, graph data, Stein method, ergodic
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Fellow to develop and evaluate artificial intelligence methods for physical medical procedures. The fellow will design and implement machine learning models to analyze procedural data, support clinical
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supervision of Prof. Flavio Calmon at Harvard SEAS. The postdoctoral researcher will develop information-theoretic methods for alignment, privacy, and reliability in modern AI systems. Basic Qualifications
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psychometric testing; leading and contributing to peer-reviewed journal publications; publishing and presenting findings to a wide variety of audiences using different methods; activities to translate research
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School is conducting research at the interface human and artificial intelligence. We create methods and tools that enable humans and machines alike to interact with and generate insights from biomedical
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. Research areas include Representation Learning, Machine learning and Optimization on graphs and manifolds, as well as applications of geometric methods in the Sciences. This is a one-year position with