Internship - Multi-modal sensor fusion for predictive maintenance

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    Mitsubishi Electric Research Laboratories

    51-200 employeesFounded 1991Cambridge, MAResearch
    Actively hiringPaidVisa sponsorshiprollingResearch
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    Best applied by Sep 13

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    About the role#

    Mitsubishi Electric Research Laboratories is looking for a Ph.D. candidate to join our team for a 3-month internship. You will focus on developing machine learning algorithms to fuse multi-modal time sequence data for electric machine condition monitoring and predictive maintenance. This position is based in Cambridge, Massachusetts.

    What you'll do#

    • Collaborate with researchers to design and develop novel algorithms.
    • Develop machine learning models for condition monitoring.
    • Prepare technical reports on your findings.
    • Contribute to manuscripts for scientific publications.

    What you'll need#

    • You are a Ph.D. candidate in Computer Science, Electrical Engineering, or a related field.
    • Strong background in machine learning and signal processing.
    • A proven publication record.
    • Experience with time-sequence analysis, multi-modal sensor fusion, or physics-informed machine learning.
    • Knowledge of electric machines is a plus.

    Location & details#

    • Location: Cambridge, MA.
    • Work modality: On-site.
    • Term: Rolling.
    • Employment type: Full-time.
    • Compensation: 6,000 to 8,000 dollars per month.
    • Benefits: Includes a relocation stipend, travel coverage, a monthly Charlie Card, and health insurance eligibility after 90 days.
    • Sponsorship: Available for qualified candidates.

    About Mitsubishi Electric Research Laboratories

    Mitsubishi Electric Research Laboratories is the United States subsidiary of the corporate research and development division of Mitsubishi Electric Corporation. Founded in 1991 and based in Cambridge, Massachusetts, the organization employs between 51 and 200 people. It conducts basic and applied research in fields such as artificial intelligence, signal processing, and multi-physical modeling. The laboratory publishes its findings to support collaboration with the global research community.

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