Internship - Generative Modeling, Inference, and Uncertainty Quantification

The Computational Sensing team at Mitsubishi Electric Research Laboratories (MERL) is seeking a highly motivated PhD student for a research internship focused on generative modeling, probabilistic inference, and optimization. Potential research directions include diffusion and flow-based generative models, efficient and controllable generation, Bayesian inference and uncertainty quantification, and generative methods for optimization.

Applications may include materials and molecular discovery, inverse design, imaging, and modeling of complex physical and dynamical systems. Specific research topics will be developed collaboratively based on mutual interests and expertise. We particularly value creativity, strong mathematical and computational skills, independent thinking, and complementary expertise across disciplines. Publication of research results is expected.

The internship is anticipated to last at least 3 months, with a flexible start date. Specific Requirements: PhD student in computer science, applied mathematics, statistics, computational chemistry, materials science, engineering, or a related field. Strong research background in one or more of the following areas: generative modeling, probabilistic machine learning, stochastic processes, optimization, or computational modeling of physical and molecular systems.

Proficiency in Python and experience with modern machine learning frameworks or scientific computing tools. The pay range for this internship position will be 6-8K per month. Mitsubishi Electric Research Labs, Inc. "MERL" provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, MERL complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training. MERL expressly prohibits any form of workplace harassment based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.

Improper interference with the ability of MERL’s employees to perform their job duties may result in discipline up to and including discharge. Working at MERL requires full authorization to work in the U.S and access to technology, software and other information that is subject to governmental access control restrictions, due to export controls. Employment is conditioned on continued full authorization to work in the U.S and the availability of government authorization for the release of these items, which might include without limitation, obtaining an export license or other documentation.

MERL may delay commencement of employment, rescind an offer of employment, terminate employment, and/or modify job responsibilities, compensation, benefits, and/or access to MERL facilities and information systems, as MERL deems appropriate, to ensure practical compliance with applicable employment law and government access control restrictions. In addition to base pay, interns receive a relocation stipend, covered travel to and from MERL, and a monthly Charlie Card for local commuting.

Interns are invited to participate in weekly social gatherings and professional development opportunities, including research talks by both internal and external speakers. Interns who meet the 90-day waiting period are also eligible for health insurance coverage. MERL provides immigration support for qualified candidates as needed. Employment is considered “at-will,” and the Company reserves the right to modify base salary or any other compensation program at any time, including for reasons related to individual performance, departmental or Company performance, and market conditions.