23 condition-monitoring-machine-learning Postdoctoral positions at Harvard University
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is currently building and commissioning a network of calibrated multi-sensor observatory-class systems, and developing novel machine learning methods with the aim of collecting science-quality data
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areas: Generative AI Agentic AI Graph Representation Learning and Modeling Foundation Models Large Language Models Multimodal Learning Basic Qualifications A Ph.D. or equivalent degree in Machine Learning
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orientation, religion, creed, national origin, ancestry, age, protected veteran status, disability, genetic information, military service, pregnancy and pregnancy-related conditions, or other protected status
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of biomechanics and computer vision to document the wingbeat frequencies and phototactic behaviors of diverse insects under diverse contexts. Candidates will be expected to plan and lead behavioral experiments
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data in near-term era quantum computers. Applicants with backgrounds in quantum information or particle physics are both encouraged to apply. Candidates with strong expertise in machine learning, quantum
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additionally learn a cutting-edge technique called cyclic immunofluorescence (CyCIF), which allows spatial resolution of different cell states within a tissue in order to understand how tumors are organized and
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related to DNA protein interactions monitored using bulk and single molecule techniques. The appointment duration is up to three years, with reappointment contingent upon funding and research collaboration
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information, military service, pregnancy and pregnancy-related conditions, or other protected status. Minimum Number of References Required 2 Maximum Number of References Allowed 3 Keywords optics, protein
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related to DNA protein interactions monitored using bulk and single molecule techniques. The appointment duration is up to three years, with reappointment contingent upon funding and research collaboration
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. Successful candidates will be expected to contribute to technique development/material synthesis, plan and lead research projects, acquire and analyze experimental data, supervise and mentor undergraduate