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Staff - Research Scientist - Optimization Algorithms
Department: OR - Optimization and Intelligent Robotics
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.
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