Internship - Multi-Fidelity Dynamic Models for Energy Systems

2 weeks ago


Cambridge, Massachusetts, United States Mitsubishi Electric Research Laboratories Full time

MERL seeks a motivated graduate student to develop multi-fidelity dynamic simulation methods for energy systems (e.g., vapor-compression/HVAC cycles and related multiphysics platforms). Candidates should have hands-on time-domain numerical simulation experience (ODE/DAE integration, implicit/iterative solvers, sparse linear algebra), familiarity with model reduction or surrogate modeling, solid thermofluids literacy (thermodynamics, heat transfer, fluid mechanics), and strong programming skills in Python/Julia/Matlab. System identification and/or numerical optimization for dynamical systems, and familiarity with equation-oriented tools (Modelica or Simscape), are desirable; a track record of rigorous research (papers or robust software) is preferred. Senior PhD students in applied mathematics, chemical/mechanical engineering, or related areas are encouraged to apply. The internship is 3 months, with a flexible start date.

The pay range for this internship position will be 6-8K per month.

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.

In addition to base pay, interns receive a relocation stipend, covered travel to and from MERL, and a monthly Charlie Card for local commuting. Interns are invited to participate in weekly social gatherings and professional development opportunities, including research talks by both internal and external speakers. Interns who meet the 90-day waiting period are also eligible for health insurance coverage. MERL provides immigration support for qualified candidates as needed. Employment is considered �at-will,� and the Company reserves the right to modify base salary or any other compensation program at any time, including for reasons related to individual performance, departmental or Company performance, and market conditions.



  • Cambridge, Massachusetts, United States Mitsubishi Electric Research Laboratories Full time

    The Computational Sensing team at MERL is seeking a highly motivated Ph.D. student for a research internship in machine learning for fluid dynamics, focusing on surrogate modeling of free-surface flows in engineered geometries. The goal of this project is to develop geometry-aware and physics-informed surrogate models for complex flow systems, combining...


  • Cambridge, Massachusetts, United States Mitsubishi Electric Research Laboratories Full time

    MERL is seeking a highly motivated and qualified intern to conduct research on applying foundation models to robotic manipulation. The focus will be on leveraging large-scale pretrained models (e.g., vision-language models, multimodal transformers, diffusion policies) to enable generalist manipulation capabilities across diverse objects, tasks and...


  • Cambridge, Massachusetts, United States Mitsubishi Electric Research Laboratories Full time

    MERL is looking for a highly motivated and qualified PhD student in the areas of system identification, to participate in research on advanced algorithms for system identification of mechanical systems and processes. Solid background and hands-on experience with various system identification algorithms is required, including black-box and grey-box methods....


  • Cambridge, Massachusetts, United States Mitsubishi Electric Research Laboratories Full time

    MERL is looking for research interns to conduct research into building and training novel architectures for small (~1 billion parameters) vision + language models. Interesting research directions include (a) diffusion and flow matching-based architectures, (b) architectures for improved visual reasoning, and (c) reducing confabulation using...


  • Cambridge, Massachusetts, United States Softcom Systems Inc Full time

    Must have skills:BE in Electrical EngineeringExperience in Power Systems Applications (PSA), Energy Management Systems (EMS), or SCADA integration.Proven experience with GE AEMSeTerra environments is required.Strong understanding of power system operations, network modeling, and realtime data processing.Detailed Job Description:BE in Electrical...


  • Cambridge, Massachusetts, United States Mitsubishi Electric Research Laboratories Full time

    MERL is looking for a highly motivated intern to work on an original research project in reconstruction/rendering dynamic 3D scenes. A strong background in 3D computer vision and/or computer graphics is required. Experience in the latest advances of deep learning in this area, such as neural radiance fields (NeRFs)/Gaussian Splatting (GS)/Point Map...


  • Cambridge, Massachusetts, United States Mitsubishi Electric Research Laboratories Full time

    We are seeking graduate students interested in helping advance the fields of generative audio, source separation, speech enhancement, and robust ASR in challenging multi-source and far-field scenarios. The interns will collaborate with MERL researchers to derive and implement new models and optimization methods, conduct experiments, and prepare results for...


  • Cambridge, Massachusetts, United States Mitsubishi Electric Research Laboratories Full time

    MERL is looking for a self-motivated intern to work on anomaly localization in industrial inspection setting using computer vision. The relevant topics in the scope include (but not limited to): cross-view image anomaly localization, how to train one model for multiple views and defect types, how to incorporate large foundation models in image anomaly...


  • Cambridge, Massachusetts, United States The Charles Stark Draper Laboratory Full time

    Overview:Draper is an independent, nonprofit research and development company headquartered in Cambridge, MA. The 2,000+ employees of Draper tackle important national challenges with a promise of delivering successful and usable solutions. From military defense and space exploration to biomedical engineering, lives often depend on the solutions we provide....


  • Cambridge, Massachusetts, United States Mitsubishi Electric Research Laboratories Full time

    MERL is seeking a motivated and qualified individual to conduct research in analysis and optimization of hybrid vehicles. The ideal candidate should have solid backgrounds in hybrid electrical propulsion system modeling and analysis, optimization, and optimal control. Excellent coding skills on MATLAB and/or python is a necessity. Ph.D. students in aerospace...