Internship Openings

5 / 36 Intern positions were found.

Mitsubishi Electric Research Labs, Inc. "MERL" provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, MERL complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

MERL expressly prohibits any form of workplace harassment based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. Improper interference with the ability of MERL's employees to perform their job duties may result in discipline up to and including discharge.

Working at MERL requires full authorization to work in the U.S and access to technology, software and other information that is subject to governmental access control restrictions, due to export controls. Employment is conditioned on continued full authorization to work in the U.S and the availability of government authorization for the release of these items, which might include without limitation, obtaining an export license or other documentation. MERL may delay commencement of employment, rescind an offer of employment, terminate employment, and/or modify job responsibilities, compensation, benefits, and/or access to MERL facilities and information systems, as MERL deems appropriate, to ensure practical compliance with applicable employment law and government access control restrictions.

  • EA2094: Imaging of nano-particle

    • MERL is looking for interns for the project of magnetic particle imaging (0907-a.pdf). We expect the intern to (1) build a model that describes the magnetic particle imaging system; (2) implement a few existing reconstruction algorithms and identify their relative strengths; (3) (ideally) develop/identify the algorithm specific for the system, and/or suggest the measurement schemes for image reconstruction. Candidates are expected to have basic understanding of electromagnetic theory and solid skill of coding (Python and/or C++ and/or matlab). Students from physics, mathematics, electrical engineering or related fields are encouraged to apply.

    • Research Areas: Multi-Physical Modeling
    • Host: Chungwei Lin
    • Apply Now
  • EA2135: Transfer Learning for Fault Diagnosis

    • MERL is seeking a motivated and qualified individual to conduct research on transfer learning for fault diagnosis, to be used for industrial applications especially electric machine fault diagnosis and predictive maintenance. Ideal candidates are Ph.D. students with a solid background and publication record in one or more research areas: fault diagnosis, statistical machine learning, transfer learning and domain adaptation, and electric motors. Strong programming skills using Python/PyTorch are expected. Knowledge and background in electric machines related research is a strong plus. Start date for this internship is flexible and the duration is typically 3 months.

    • Research Areas: Electric Systems, Machine Learning, Multi-Physical Modeling
    • Host: Bingnan Wang
    • Apply Now
  • EA2050: Electric Motor Design and Electromagnetic Analysis

    • MERL is seeing a motivated and qualified individual to conduct research on electric motor design and modeling, with a strong focus on electromagnetic analysis. Ideal candidates should be Ph.D. students with solid background and publication record in one more research area on electric machines: electric and magnetic modeling, new machine design and prototyping, harmonic analysis, fault detection, and predictive maintenance. Research experiences on modeling and analysis of electric machines and fault diagnosis are required. Hands-on experience with new motor design and data analysis techniques are highly desirable. Start date for this internship is flexible and the duration is 3-6 months.

    • Research Areas: Applied Physics, Multi-Physical Modeling
    • Host: Bingnan Wang
    • Apply Now
  • MS1851: Dynamic Modeling and Control for Grid-Interactive Buildings

    • MERL is looking for a highly motivated and qualified candidate to work on modeling for smart sustainable buildings. The ideal candidate will have a strong understanding of modeling renewable energy sources, grid-interactive buildings, occupant behavior, and dynamical systems with expertise demonstrated via, e.g., peer-reviewed publications. Hands-on programming experience with Modelica is preferred. The minimum duration of the internship is 12 weeks; start time is flexible.

    • Research Areas: Machine Learning, Multi-Physical Modeling, Optimization
    • Host: Chris Laughman
    • Apply Now
  • MS1958: Simulation, Control, and Optimization of Large-Scale Systems

    • MERL is seeking a motivated graduate student to research numerical methods pertaining to the simulation, control, and optimization of large-scale systems. Representative applications include large vapor-compression cycles and other multiphysical systems for energy conversion that couple thermodynamic, fluid, and electrical domains. The ideal candidate would have a solid background in numerical methods, control, and optimization; strong programming skills and experience with Julia/Python/Matlab are also expected. Knowledge of the fundamental physics of thermofluid flows (e.g., thermodynamics, heat transfer, and fluid mechanics), nonlinear dynamics, or equation-oriented languages (Modelica, gPROMS) is a plus. The expected duration of this internship is 3 months.

    • Research Areas: Control, Multi-Physical Modeling, Optimization
    • Host: Chris Laughman
    • Apply Now