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Mitsubishi Electric Research Laboratories

Mitsubishi Electric Research Laboratories

www.merl.com

4 Jobs

130 Employees

About the Company

Mitsubishi Electric Research Laboratories (MERL) is the US subsidiary of the Corporate R&D organization of Mitsubishi Electric Corporation. MERL does basic and applied research in the areas of multi-physical modeling and simulation, optimization, control, signal processing and artificial intelligence. We are an open lab, publishing our results, collaborating with the world-wide research community, and measuring our performance by the impact we have on Mitsubishi Electric and the world.

Listed Jobs

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Company Name
Mitsubishi Electric Research Laboratories
Job Title
Internship - Stochastic Model Predictive Control with Generative Models for Smart Building Control
Job Description
Job title: Internship – Stochastic Model Predictive Control with Generative Models for Smart Building Control Role Summary: Research intern tasked with developing transformer‑informed stochastic model predictive control algorithms to manage net‑zero energy smart buildings. Must design, implement, test, and document methodologies, and produce publishable results during a 3–6 month internship. Expectations: Deliver functional MPC solutions, validate performance on real building data, contribute to research publications, and meet project milestones within a flexible start schedule. Key Responsibilities: - Design and implement transformer‑based stochastic MPC workflows. - Develop probabilistic time‑series prediction models and integrate them into control loops. - Formulate and solve convex programming formulations of MPC/SMPC problems. - Conduct performance evaluation on real or simulated building control systems. - Prepare technical documentation and author research papers for academic venues. Required Skills: - Hands‑on experience in stochastic MPC and convex optimization. - Proficiency in Python, PyTorch, and related deep‑learning frameworks. - Strong understanding of probabilistic time‑series forecasting. - Ability to translate theoretical models into efficient, deployable algorithms. Required Education & Certifications: - Master’s degree completed or >50 % of a PhD program in control systems, applied mathematics, machine learning, or a related field. - Publications in stochastic MPC or related research areas preferred.
Cambridge, United states
On site
14-02-2026
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Company Name
Mitsubishi Electric Research Laboratories
Job Title
Internship - Fine-tuning Large language models
Job Description
**Job title** Internship – Fine‑tuning Large Language Models **Role Summary** A senior Ph.D. candidate in Computer Science or Electrical Engineering will participate in a 3‑month internship focused on developing and applying multi‑modal large language models (LLMs) for anomaly detection, time‑sequence analysis, and predictive maintenance. The role involves collaborating with researchers to design LLM‑based frameworks, analyze multi‑modal sensor data, and contribute to technical reports and publishable manuscripts. **Expectations** - Completion of a Ph.D. program (computer science, electrical engineering, or related field). - Demonstrated expertise in machine learning and signal processing. - Strong publication record in top conferences/journals. - Experience or interest in fine‑tuning foundation language models. **Key Responsibilities** - Fine‑tune large language models on multi‑modal time‑sequence data sets. - Design and implement LLM‑based frameworks for sensor data analysis. - Conduct experiments, evaluate model performance, and iterate on model architectures. - Prepare technical reports, data analysis documents, and draft manuscripts for submission to academic venues. - Collaborate with research teams to integrate LLM outputs with downstream anomaly detection and predictive maintenance pipelines. **Required Skills** - Machine learning (deep learning, transformer architectures). - Large language model fine‑tuning and evaluation. - Multi‑modal time‑sequence data analysis. - Signal processing fundamentals. - Programming: Python, PyTorch/TensorFlow, data‑pipeline tools. - Strong analytical and problem‑solving abilities. **Required Education & Certifications** - Current Ph.D. candidate in Computer Science, Electrical Engineering, or a closely related discipline. ---
Cambridge, United states
On site
14-02-2026
Company background Company brand
Company Name
Mitsubishi Electric Research Laboratories
Job Title
Internship - Whole-body manipulation for quadrupedal robots
Job Description
Job Title: Internship – Whole‑Body Manipulation for Quadrupedal Robots Role Summary A Ph.D. candidate will develop and validate algorithms that enable a quadrupedal robot to locomote and simultaneously manipulate 3‑D objects located beyond its immediate workspace. The internship involves simulation work, physical‑robot experimentation, algorithm implementation, experimental analysis, and research dissemination. Expectations * Ph.D. graduate student or advanced master's student in robotics, mechanical engineering, computer science, or related field. * Strong background in legged locomotion, grasp pose detection, machine vision, and contact‑aware manipulation. * Willingness to conduct rigorous experimental validation on a real quadrupedal platform and publish findings at a top conference. Key Responsibilities * Design, implement, and evaluate loco‑manipulation algorithms in simulation (e.g., Isaac Lab, MuJoCo). * Transfer and refine algorithms for real‑world execution on a physical quadrupedal robot. * Conduct systematic experiments, collect data, and analyze performance metrics. * Prepare technical reports and conference papers; support patent preparation if applicable. * Collaborate with senior researchers and laboratory staff on multidisciplinary projects. Required Skills * Proficiency in programming (C++ or Python). * Experience with physics‑based simulation environments (Isaac Lab, MuJoCo, or equivalent). * Knowledge of robot perception, machine learning, and grasp planning. * Prior hands‑on experience with bipedal or quadrupedal robotic platforms. * Strong analytical, problem‑solving, and documentation skills. Required Education & Certifications * Current Ph.D. student (or equivalent advanced master’s level) in robotics, mechanical engineering, computer science, electrical engineering, or a related discipline. * No specific certifications required; demonstrated coursework or projects in legged robotics, manipulation, and machine learning preferable.
Cambridge, United states
On site
17-02-2026
Company background Company brand
Company Name
Mitsubishi Electric Research Laboratories
Job Title
Internship - Sensor Reasoning Models
Job Description
**Job title**: Internship – Sensor Reasoning Models **Role Summary**: Conduct foundational research on sensor reasoning models that integrate multimodal perception (RF, infrared, LiDAR, event camera) with higher‑level text, visual, and multimodal reasoning. Develop and evaluate algorithms, design experiments on in‑house testbeds, and prepare scholarly outputs (publications, patents). **Expectations**: * 3‑month internship, flexible start from October 2025. * Deliver research progress reports, algorithm prototypes, benchmark results, and draft publications/patents. * Collaborate closely with senior researchers. **Key Responsibilities**: 1. Research and develop algorithms that bridge perception (detection, segmentation, tracking) with reasoning over sensor streams. 2. Integrate LLMs/VLMs with multimodal sensor outputs (point clouds, radar heatmaps, BEV features). 3. Design and run experiments on in‑house testbeds; construct reasoning‑centric benchmarks (QA, temporal prediction). 4. Manage and analyze large multi‑sensor datasets (nuScenes, Waymo, Argoverse, MMVR, HIBER, RT‑Pose, K‑Radar). 5. Prepare results for publication in top venues and contribute to patent submissions. 6. Maintain reproducible code, scalable data pipelines, and GPU cluster job scheduling. **Required Skills**: * Proven experience in text, visual, and multimodal reasoning (e.g., VQA, temporal/spatio‑temporal reasoning, chain‑of‑thought). * Expertise aligning or conditioning LLMs/VLMs on sensor outputs (point clouds, radar). * Strong foundation in state‑of‑the‑art transformer and diffusion perception models (DETR, DiffusionDet). * Hands‑on with large multi‑sensor datasets and ability to create custom benchmarks. * Proficiency in Python and deep‑learning frameworks (PyTorch, JAX); knowledge of GPU cluster scheduling and data‑pipeline scaling. * Publication record in top-tier venues (CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML). * Understanding of sensor fundamentals (RF, infrared, LiDAR, event cameras); radar knowledge (FMCW, MIMO, Doppler signatures, point clouds). * Awareness of recent radar perception research (TempoRadar, SIRA, MMVR, RETR). **Required Education & Certifications**: * Advanced degree (MSc or PhD) in Computer Vision, Machine Learning, Robotics, or related field. * Coursework or research experience in deep learning, multimodal fusion, and sensor perception.
Cambridge, United states
On site
01-03-2026