PhD Research Internship: Generative Modeling & Uncertainty

Mitsubishi Electric Research Laboratories, Inc.; Cambridge (MA); On-site; USD 67,000 - 89,000; Full time

Benefits offered by this job

Relocation stipend

Travel coverage

Charlie Card for local commuting

Health insurance eligibility

Job summary

Mitsubishi Electric Research Laboratories (MERL) is seeking a PhD student intern to advance research in generative modeling, probabilistic inference, and optimization. Potential directions include diffusion and flow-based models, uncertainty quantification, and inverse design across materials, imaging, and dynamical systems.

The internship lasts at least 3 months with a flexible start date. Publication of results is encouraged and a relocation stipend with travel support is provided, along with

Qualifications

• Proficiency in Python and experience with modern machine learning frameworks or scientific computing tools.
• Strong research background in generative modeling, probabilistic ML, stochastic processes, optimization, or computational modeling.

Responsibilities

• Research internship focused on generative modeling, probabilistic inference, and optimization.
• Collaboration on topics like diffusion/generative models, Bayesian inference, and uncertainty quantification.
• Publications of research results are expected.

Skills

Python

Education

PhD student in Computer Science / Applied Mathematics / Statistics / Computational Chemistry / Materials Science / Engineering

Job description

Mitsubishi Electric Research Laboratories (MERL) is seeking a PhD student intern to advance research in generative modeling, probabilistic inference, and optimization. Potential directions include diffusion and flow-based models, uncertainty quantification, and inverse design across materials, imaging, and dynamical systems.

The internship lasts at least 3 months with a flexible start date. Publication of results is encouraged and a relocation stipend with travel support is provided, along with