Research Intern
Are you applying to the internship?
Job Description
About Company:
Mitsubishi Electric Research Labs, Inc. “MERL” is committed to equal employment opportunities for all employees and applicants, adhering to federal, state, and local laws regarding nondiscrimination. MERL prohibits workplace harassment and emphasizes the importance of compliance with export control restrictions, which may impact employment conditions.
Job Description:
MERL is seeking a Research Intern to contribute to the development of efficient transformer-informed stochastic Model Predictive Control (MPC) for controlling net-zero energy buildings. This internship offers the opportunity to work on a cutting-edge project involving deep learning and predictive control applied to a real-world system. The internship aims for a real-world impact and desires publications of results.
Key Aspects:
• Focus: Developing efficient transformer-informed stochastic MPC for net-zero energy building control.
• Technology: Deep learning, predictive control, stochastic MPC, Transformers.
• Impact: Real-world application with potential for publication.
• Duration: 3-6 months, with a flexible start date.
Ideal Candidate Profile:
• Significant hands-on experience with stochastic MPC.
• Publications in SMPC are a strong plus.
• Fluency in Python and PyTorch.
• Understanding of probabilistic time-series prediction.
• Experience with convex programming.
• Convex formulations of MPC/SMPC problems are a strong plus.
• Completed their MS, or >50% of their PhD program.
