Employment Openings
We are always on the lookout for exceptional scientists and engineers to join MERL.
With offices in Cambridge, MA, we offer a collaborative research environment with excellent benefits where talented people apply their skills and grow professionally. For students, we give scores of interns every year an opportunity to participate in exciting research in a stimulating environment with the likelihood of a publication as a result.
For a flavor of what MERL is like, browse our people, projects and publications pages. We also invite you to read the welcome letter from our Chairman, Dr. Anthony Vetro, which will give you a sense of the company culture. If you have an interest in working at MERL please submit your resume using the "apply online" button for one of the job openings below.
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.
Current Openings
- OR0052: Research Scientist - Optimization Algorithms
- CA0093: Research Scientist - Control for Autonomous Systems
OR0052: Research Scientist - Optimization Algorithms
Our team addresses optimization problems arising from a variety of domains including electric grids, drones, transportation, and supply chain management. The applications of interest encompass the problem classes of continuous non-convex nonlinear programs and mixed-integer nonlinear programs.
We are seeking candidates who can perform fundamental research in developing novel optimization algorithms, analysis of algorithms, incorporate machine learning techniques for improving performance of algorithms, and implementation of algorithms that can be deployed in application specific processing environments ranging from embedded processors to massively parallel architectures.
The candidate will have an opportunity to learn about the specific application domains above and is expected to tailor algorithms for computational performance. Longer term interests also include the study of quantum processors and their impact on optimization in general. The successful candidate is expected to perform leading research in this area, to demonstrate it through application to one or more of the domains above, to publish in top conferences and journals, and to develop over the years a fundamental research agenda aimed at impacting the scientific community and the Mitsubishi Electric's future technology.
Responsibilities for this position include:
- Conducting innovative and relevant research in optimization algorithms, possibly with applications to electric grids, transportation, and supply chain optimization,
- Developing a research agenda impacting both the scientific community and the future company technology,
- Publishing results in leading technical journals, conferences, and in patent applications,
- Applying the research results to company-relevant R&D projects,
- Collaborating with research staff, academic partners, and mentoring interns,
- Transferring results and technology to Mitsubishi Electric corporate research laboratories.
Qualifications for this position are:
- A Ph.D. from an internationally-recognized institution in computer science, mathematics, numerical analysis, or chemical, industrial engineering, electrical, or a related discipline, with a focus on optimization,
- A strong publication record, consistent with experience,
- Extensive knowledge of a numerical optimization algorithms for convex programming and possibly mixed integer programming,
- Strong programming skills, in at least some of C/C++, Python, Julia, Matlab,
- Strong teamwork, communication, listening and teaching skills.
- Seniority of the candidate will be considered to determine the position level. Interested parties must submit a cover letter and an up to one-page statement of research interests.
PRINCIPALS ONLY Apply Online. No phone calls please.
Mitsubishi Electric Research Laboratories, Inc. is an Equal Opportunity Employer.
CA0093: Research Scientist - Control for Autonomous Systems
Mitsubishi Electric Research Laboratories (MERL), the US research organization of Mitsubishi Electric Corporation, is looking for a talented researcher to join the Control for Autonomy Team. MERL conducts fundamental research motivated by real-world problems, and then applies the results to demonstrate the solutions of such problems. MERL encourages publishing and presenting research results, and collaborating with academia and the scientific community. The Control for Autonomy Team focuses on planning, control and estimation for autonomous systems leveraging novel fundamental research in control theory, optimization, estimation and machine learning.
The research areas for the open position include, but are not limited to, design with guarantees and analysis of machine learning-based controllers, perception (e.g., vision, point-cloud, ...) based planning and control, control for human-in-the-loop and human-machine interaction, real-time optimization algorithms, statistical learning and estimation, and constrained control. Candidates at any career stage are considered, with title and role adjusted based on prior experience.
Responsibilities for this position include:
- Conduct innovative fundamental research in the areas of control and planning for autonomous systems, and apply the research results in relevant domains.
- Validate the research results by simulations and possibly experiments with prototypes/lab equipment.
- Publish results in leading technical journals and conferences, and support drafting patent applications.
- Support technology transfer to partner organizations such as advanced engineering and product development labs.
- Define new long-term research directions and propose and lead research projects.
Qualifications for this position are:
- Ph.D. from an internationally recognized institution in Electrical Engineering, Mechanical Engineering, Aerospace Engineering, Computer Science or Applied Mathematics or other relevant fields, with a focus on control theory and/or machine learning.
- Strong publication record demonstrating innovative research.
- Strong programming skills in at least one of Python, Matlab, C/C++, Julia. Basic knowledge or interest in real-time/embedded systems programming is a plus, but not required.
- Interest in experimental validation of research results, e.g., with drones, small ground robots, legged robots. Prior experience in experimental validation is a plus, but not required.
- Teamwork, communication (oral, and written) and presentation skills.