Internship Openings

14 / 58 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.

Qualified applicants for MERL internships are individuals who have or can obtain full authorization to work in the U.S. and do not require export licenses to receive information about the projects they will be exposed to at MERL. The U.S. government prohibits the release of information without an export license to citizens of several countries, including, without limitation, Cuba, Iran, North Korea, Sudan and Syria (Country Groups E:1 and E:2 of Part 740, Supplement 1, of the U.S. Export Administration Regulations).


  • SP1430: WiFi Sensing

    • The Signal Processing (SP) group at MERL is seeking a highly motivated intern to conduct fundamental research in wireless sensing using communication signals such as 5G, WiFi, and Bluetooth. Previous experience on occupancy sensing, people counting, localization, device-free pose/gesture recognition with machine learning approaches is highly preferred. Familiarity with IEEE 802.11 (ac/ad/ay)standards is a plus. The intern will collaborate with a small group of MERL researchers to develop novel algorithms, collect real-world channel measurements, and prepare results for publication. Senior Ph.D. students with research focuses on wireless communications, machine learning, signal processing, optimization, applied mathematics, or related areas are encouraged to apply. The expected duration of the internship is 3 months with a flexible start date.

    • Research Areas: Artificial Intelligence, Communications, Computational Sensing, Data Analytics, Dynamical Systems, Machine Learning, Optimization, Signal Processing
    • Host: Perry Wang
    • Apply Now
  • SP1431: Multi-view image processing

    • MERL is looking for a self-motivated intern to work on multi-view image processing. The ideal candidate would be a senior Ph.D. student in electrical engineering or computer science with solid research background in image processing such as enhancement, registration, and distortion correction, etc. Experience in sparse modeling is desirable. Proficiency in MATLAB and Python is necessary. The intern is expected to collaborate with MERL researchers to build models, develop algorithms, and prepare manuscripts for scientific publications. The total duration is 3 months.

    • Research Areas: Computer Vision, Optimization, Signal Processing
    • Host: Dehong Liu
    • Apply Now
  • MP1406: Numerical Analysis of Electric Machines

    • MERL is seeking a motivated and qualified intern to conduct research in the design, modeling and optimization of electrical machines. The ideal candidate should have solid backgrounds in electromagnetic theory, electric machine design, and numerical modeling techniques (including model reduction), research experiences in electric, magnetic, and thermal modeling and analysis of electrical machines, and demonstrated capability to publish results in leading conferences/journals. Experience with ANSYS, COMSOL, and optimization techniques is a strong plus. Senior Ph.D. students in electrical or mechanical engineering with related expertise are encouraged to apply. Start date for this internship is flexible and the duration is 3-6 months.

    • Research Areas: Dynamical Systems, Multi-Physical Modeling, Optimization
    • Host: Bingnan Wang
    • Apply Now
  • CD1260: Model Predictive Control of Hybrid Systems

    • The Control and Dynamical Systems (CD) group at MERL is seeking a highly motivated intern to work on hybrid model predictive control. The scope of work includes the development of model predictive control algorithms for hybrid dynamical systems, switched systems, and quantized systems, analysis and property proving, and applications in automotive, space systems, and energy systems. PhD students with expertise in some among control, optimization, model predictive control and hybrid systems, and with working knowledge of Matlab implementation are welcome to apply. The expected duration of the internship is 3-6 months with flexible start date.

    • Research Areas: Control, Dynamical Systems, Optimization
    • Host: Stefano Di Cairano
    • Apply Now
  • CD1405: Mechanism design for mobility

    • Mobility; externalities; mechanism design. We are looking for a talented and driven individual to help us design an efficient and equitable mobility solution. This position requires a deep understanding of mechanism design and at least some programming ability. Preference will be given to candidates with a background in transportation.

    • Research Areas: Optimization
    • Host: Uroš Kalabić
    • Apply Now
  • CD1388: Mixed-Integer Optimal Control Algorithms

    • MERL is looking for highly motivated individuals to work on efficient numerical algorithms and applications of mixed-integer optimal control methods. The research will involve some among the following: the study and development of mixed-integer optimization techniques for optimal control, the implementation and validation of algorithms for relevant control applications. The ideal candidate should have experience in branch-and-bound methods and presolve techniques for mixed-integer optimization and/or model predictive control. PhD students in engineering or mathematics with a focus on mixed-integer optimization or numerical optimal control are encouraged to apply. Publication of relevant results in conference proceedings and journals is expected. Capability of implementing the designs and algorithms in Matlab is expected; coding parts of the algorithms in C/C++ is a big plus. The expected duration of the internship is 3-6 months and the start date is flexible.

    • Research Areas: Control, Dynamical Systems, Optimization
    • Host: Rien Quirynen
    • Apply Now
  • CD1412: Control of Space Vehicles

    • The Control and Dynamical Systems (CD) group at MERL is seeking a highly motivated intern for a research position in control of space vehicles. The ideal candidate is working towards a Ph.D. in aerospace, mechanical, or electrical engineering, and has background in both optimization-based control and space vehicle dynamics. The candidate is expected to possess strong abilities in algorithm analysis and Matlab implementation. The duration of the internship is approximately 3 months. Publication of results produced during the internship is expected.

    • Research Areas: Control, Dynamical Systems, Optimization
    • Host: Avishai Weiss
    • Apply Now
  • CD1300: Compiler Optimizations for Linear Algebra Kernels

    • MERL is looking for a highly motivated individual to work on automatic, compiler based techniques for optimizing linear algebra kernels. The ideal candidate is a Ph.D. student in computer science with extensive experience in compiler design and source code optimization techniques. In particular, the successful candidate will have a strong working knowledge of polyhedral optimization techniques, the LLVM compiler, and Polly. Strong C/C++ skills and knowledge of LLVM at the source level are required. Publication of results in conference proceedings and journals is expected. The expected duration of the internship is 3 months and the start date is flexible.

    • Research Areas: Control, Machine Learning, Optimization
    • Host: Bram Goldsmith
    • Apply Now
  • CD1399: Optimization Algorithms for Stochastic Predictive Control

    • MERL is looking for a highly motivated individual to work on tailored numerical optimization algorithms and applications of stochastic learning-based model predictive control (MPC) methods. The research will involve the study and development of novel optimization techniques and/or the implementation and validation of algorithms for industrial applications, e.g., related to autonomous driving. The ideal candidate should have experience in either one or multiple of the following topics: stochastic MPC (e.g., scenario trees or tube MPC), convex and non-convex optimization, machine learning, numerical optimization and (inverse) optimal control. PhD students in engineering or mathematics with a focus on stochastic (learning-based) MPC or numerical optimization are encouraged to apply. Publication of relevant results in conference proceedings and journals is expected. Capability of implementing the designs and algorithms in Matlab is expected; coding parts of the algorithms in C/C++ is a plus. The expected duration of the internship is 3-6 months and the start date is flexible.

    • Research Areas: Control, Machine Learning, Optimization
    • Host: Rien Quirynen
    • Apply Now
  • CD1401: Formal Synthesis for Planning and Control for Autonomous Systems

    • The Control and Dynamical Systems (CD) group at MERL is seeking a highly motivated intern to conduct research on planning and control by formal methods, in particular temporal logics specifications and their synthesis by mixed-integer inequalities. The ideal candidate is enrolled in a PhD program in Electrical, Mechanical, Aerospace Engineering, Computer Science or related program, with focus on Control Theory. The ideal candidate will have experience in (one or more of) formal methods, particularly temporal logics and signal temporal logics, reachability analysis, abstractions of dynamical systems, hybrid predictive control, and mixed integer programming. Good programming skills in Matlab (or alternatively Python) are required, working knowledge of C/C++ is a plus. The expected duration of the internship is 3-6 months with flexible start date after April 1st, 2020.

    • Research Areas: Control, Optimization, Robotics
    • Host: Stefano Di Cairano
    • Apply Now
  • CD1382: Motion Planning in Dynamic Environment

    • MERL is seeking a highly skilled and self-motivated intern to work on motion planning of nonholonomic system in dynamic environments. The ideal candidate should have solid backgrounds in task allocation, scheduling, and motion planning under dynamic and stochastic environment. Excellent coding skill and strong publication records are necessary. Senior Ph.D. students in control, computer science, or related areas are encouraged to apply. Start date for this internship is flexible, and the expected duration is about 3 months.

    • Research Areas: Control, Optimization, Robotics
    • Host: Yebin Wang
    • Apply Now
  • CD1402: Predictive control for Performance and Perception Optimization

    • The Control and Dynamical Systems (CD) group at MERL is seeking a highly motivated intern to conduct research on stochastic planning and control for concurrently achieving control performance while concurrently improving the perception of the environment. The ideal candidate is enrolled in a PhD program in Electrical, Mechanical, Aerospace Engineering, Computer Science or related program, with focus on Control Theory. The ideal candidate will have experience in (one or more of) predictive control or model-based motion planning, stochastic control and estimation, interaction between control and estimation algorithms, control with chance constraints, tube-based control. Good programming skills in Matlab (or alternatively Python) are required, working knowledge of C/C++ is a plus. The expected duration of the internship is 3-6 months with flexible start date after April 1st, 2020.

    • Research Areas: Control, Optimization, Robotics
    • Host: Stefano Di Cairano
    • Apply Now
  • CD1392: Statistical Estimation, Learning, and Control of Dynamical Systems

    • The Control and Dynamical Systems (CD) group at MERL is seeking a highly motivated intern to conduct fundamental research on statistical estimation and control. The scope of the internship includes development of algorithms and property proving for estimation and control of stochastic dynamical systems. PhD students with expertise in several of sequential Monte Carlo methods, Gaussian processes, Gaussian-process state-space models, model predictive control, are welcome to apply. The candidate is expected to be proficient in Matlab, and publication of the results produced during the internship is expected. The internship duration is 3 months with flexible start date.

    • Research Areas: Control, Machine Learning, Optimization
    • Host: Karl Berntorp
    • Apply Now
  • SA1031: Distributed auctions for network welfare maximization

    • We are looking for a talented individual to collaborate and facilitate research on new algorithms in mechanism design and distributed auctions. Responsibilities will include mathematical modeling, algorithm design, software prototyping, and running Monte Carlo simulations in a network traffic domain. Candidates should be strong scientific programmers and have some background in numerical optimization, simulation design, and auction theory.

    • Research Areas: Optimization
    • Host: Matt Brand
    • Apply Now