70 algorithm-phd "INSAIT The Institute for Computer Science" Fellowship positions at Harvard University
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application to lineage tracing Algorithms for characterizing structural alterations in bulk and single cell whole-genome data Mutational signature analysis for cancer/brain samples Analysis of repetitive
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-photonic computing architectures; Silicon-photonic network architectures Machine Learning Algorithms/Systems: Experience in design and use of ML algorithms; Experience in using ML for designing computing
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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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the PhD no earlier than July 31, 2021. For candidates who will have completed the PhD within twelve months of the August 1, 2026 start date, verification of completion of the degree will be required prior
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the number of years post-PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines . With this appointment, you are represented by the Harvard Academic Workers (HAW) – UAW for purposes
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welcome applications from recent PhD graduates interested in this field. The successful candidate will work to develop an independent research project within the scope of the lab’s research focus. In
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welcome applications from recent PhD graduates interested in this field. The successful candidate will work to develop an independent research project within the scope of the lab’s research focus. In
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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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inthe Livingstone lab at Harvard Medical School in Boston Massachusetts. The work of the lab is focused on primate inferotemporal cortex. We welcome applications from recent PhD graduates who
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of Engineering and Applied Sciences. The fellow will design and run human experiments, perform data analysis, and create computational models of learning and memory. A PhD is required. An ideal candidate will be