Internship Openings

Efficient Foundation Models for Edge Intelligence

We are seeking passionate and skilled interns to join our cutting-edge research team at Mitsubishi Electric Research Laboratories (MERL), focusing on efficient and sustainable AI. This internship offers a unique opportunity to contribute to next-generation machine learning techniques that enable real-time, edge, and energy-efficient AI systems — with the ultimate goal of publishing at top-tier AI venues.

Research Focus Areas

• Edge AI, real-time AI, and compact neural architectures

• Energy-efficient and hardware-friendly AI

• On-device, on-premise, and embedded-system AI

• Generative and multi-modal foundation models with resource constraints

Qualifications

• Advanced research experience in generative models, efficient architectures, or foundation models (LLM, VLM, LMM, FoMo)

• Strong understanding of state-of-the-art machine learning and optimization techniques

• Proficiency in Python and PyTorch, with familiarity in other deep learning frameworks

• Proven research record and motivation for publication in leading AI conferences

Internship Details

• Duration: Approximately 3 months

• Start Date: Flexible

• Objective: Conduct high-quality research leading to publications in premier AI conferences

If you are a highly motivated researcher eager to push the boundaries of efficient and sustainable AI, we encourage you to apply. Join us in shaping the future of intelligent systems that are not only powerful but also responsible and sustainable.

The pay range for this internship position will be 6-8K per month.

MERL is seeking a highly motivated and qualified intern to carry out research on UAV assisted IoT network methodology. The candidate is expected to develop innovative path planning technologies to support UAV swarm navigation in IoT network environments. The candidates should have knowledge of communication network technologies such as path planning and cooperative network operations. Knowledge of control technology and path management is a plus. Start date for this internship is flexible and the duration is about 3 months.

Responsibilities for this position include:

• Research on UAV assisted IoT networks
• Develop path planning technologies to support UAV coordination in IoT networks
• Simulate and analyze the performance of developed technology

Qualifications for this position are:

• Junior and senior year Ph.D students

The pay range for this internship position will be 6-8K per month.

MERL is seeking a highly motivated and qualified intern to conduct research on multi-hop IoT network anomaly detection and analysis. The candidate is expected to develop innovative network anomaly detection technologies that can proactively detect and analyze network failure in multi-hop IOT networks. The candidate should have knowledge of LLM/ML and anomaly detection. Knowledge of network log analysis and network protocol a plus. Start date for this internship is flexible and the duration is about 3 months.

Responsibilities for this position include:

• Research on anomaly detection in multi-hop IoT networks
• Develop innovative network anomaly detection and analysis technologies
• Simulate and analyze the performance of developed technology

Qualifications for this position are:

• Junior and senior year Ph.D candidates

The pay range for this internship position will be 6-8K per month.

PRINCIPALS ONLY. No phone calls please.

Mitsubishi Electric Research Laboratories, Inc. is an Equal Opportunity Employer.

Mitsubishi Electric Research Laboratories (MERL) is seeking a self-motivated Ph.D. candidate in Computer Science, Electrical Engineering, or a related field for a 3 month internship focused on developing advanced machine learning algorithms for electric machine condition monitoring and predictive maintenance. The ideal candidate will have a strong background in machine learning and signal processing with a proven publication record, while experience in multi-modal data analysis or domain adaptation is preferred and knowledge of electric machines is a plus. The intern will collaborate with MERL researchers to design and develop novel machine learning algorithms, prepare technical reports, and contribute to manuscripts for top-tier scientific publications. This position requires onsite work at MERL, with a flexible start date.

Required Specific Experience

• Experience with Python and Matlab.

The pay range for this internship position will be 6-8K per month.

We are seeking graduate students interested in advancing the fields of spatial audio, room acoustics, physics informed machine learning, and scene understanding (e.g., sound source localization and spatial-aware captioning). The interns will work closely with MERL researchers to develop novel algorithms, record data, conduct experiments, and prepare results for publication. Internships regularly lead to one or more publications in top-tier venues, which can later become part of the intern's doctoral work. The ideal candidates are senior Ph.D. students with experience in some of the following: microphone array processing, physics informed machine learning, and 3D modeling in computer vision. Multiple positions are available with flexible start date (not just Spring/Summer but throughout 2026) and duration (typically 3-6 months).

The pay range for this internship position will be6-8K per month..

We are seeking graduate students interested in helping advance the fields of machine sound source separation, sound event detection/localization, anomaly detection, and physics informed deep learning for machine sounds in extremely noisy conditions. The interns will collaborate with MERL researchers to derive and implement novel algorithms, record data, conduct experiments, integrate audio signals with other sensors (electrical, vision, vibration, etc.), and prepare results for publication. Internships regularly lead to one or more publications in top-tier venues, which can later become part of the intern's doctoral work.

The ideal candidates are senior Ph.D. students with experience in some of the following: audio signal processing, audio source separation (music, speech, or general sounds), microphone array processing, sound event localization and detection, anomaly detection, and physics informed machine learning.

Multiple positions are available with flexible start dates (not just Spring/Summer but throughout 2026) and duration (typically 3-6 months).

The pay range for this internship position will be6-8K per month.

The Computational Sensing Team at MERL is seeking an intern to work on estimation algorithms for single-photon lidar. The ideal candidate would be a PhD student with a strong background in statistical modeling, estimation theory, computational imaging, and/or inverse problems. The intern will collaborate with MERL researchers to design new lidar reconstruction algorithms, conduct simulations, and prepare results for publication. A detailed knowledge of single-photon detection, lidar, and Poisson processes is preferred. Hands-on optics experience may be beneficial but is not required. Strong programming skills in Python or MATLAB are essential. The duration is anticipated to be 3 months with a flexible start date.

The pay range for this internship position will be 6-8K per month.

The Computational Sensing team at MERL is seeking motivated and qualified individuals to develop algorithms that can perform background oriented schlieren (BOS) tomography. The project goal is to utilize both analytical and learning-based architectures to enable the reconstruction of 3D air flows in an indoor setting from BOS measurements coupled with physics informed machine learning. Ideal candidates should be Ph.D. students and have solid background and publication record in any of the following, or related areas: imaging inverse problems, large-scale optimization, differentiable scene rendering, learning-based modeling for imaging, and physics informed neural networks. Preferred skills include experience with schlieren tomography, inverse rendering, neural scene representation, computational imaging hardware, and computationally efficient optimization of PINNs. Publication of the results produced during our internships is expected. The duration of the internships is anticipated to be 3-6 months. Start date is flexible.

Required Specific Experience

• Experience with differentiable/physics-based rendering.

The pay range for this internship position will be 6-8K per month.

MERL is seeking a motivated intern to assist in developing hardware and algorithms for multimodal imaging applications. The project involves integration of radar, camera, and depth sensors in a variety of sensing scenarios. The ideal candidate should have experience with FMCW radar and/or depth sensing, and be fluent in Python and scripting methods. Familiarity with optical tracking of humans and experience with hardware prototyping is desired. Good knowledge of computational imaging and/or radar imaging methods is a plus.

Required Specific Experience

• Experience with Python and Python Deep Learning Frameworks.
• Experience with FMCW radar and/or Depth Sensors.

The pay range for this internship position will be 6-8K per month.