884 embedded-system "https:" "https:" "https:" "https:" "Grenoble INP Institute of Engineering" positions at Harvard University
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at Harvard Medical School in Boston, Massachusetts. The work of the Gygi lab is focused on developing and applying mass spectrometry-based approaches to the drug discovery pipeline. We welcome applications
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Details Title Postdoctoral Fellow in On-Premise Computing for Autonomous Vehicles (Computer Architecture, Machine Learning and Runtime Systems) School Harvard John A. Paulson School of Engineering
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: 16141 School: Harvard John A. Paulson School of Engineering and Applied Sciences Position Description: The Aizenberg Lab at Harvard University is seeking a postdoctoral researcher to join a
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: Harvard John A. Paulson School of Engineering and Applied Sciences Position Description: The Y-Lab is seeking a postdoctoral fellow for projects in the following areas: Optical-to-optical quantum frequency
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research proposal, and two to three references’ names and contact information. Applications must be received by 4/15/26. For more information, please visit our website – https
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. Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines . Minimum Number of References
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Details Title Postdoctoral Fellow in Energy System Optimization and Digitization School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position Description
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Machine Learning Group’s website: https://weber.seas.harvard.edu Contact Email mweber@seas.harvard.edu Salary Range $67,600 – $91,826 Pay offered to the selected candidate is dependent on factors such as
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Genomics at Harvard Medical School Several positions are available in the Park Lab (https://compbio.hms.harvard.edu/ ). The aim of the laboratory is to develop and apply innovative computational methods
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Experience with finetuning embedding models and tuning vector databases to improve performance of semantic search and retrieval systems Experience operationalizing end-to-end machine learning applications