Staff - Postdoctoral Research Fellow - AI for Science

Job Description

Job Description

MERL is seeking a highly motivated Postdoctoral Research Fellow in AI for Science to join our research team. This position offers a distinctive opportunity for early-career researchers to pursue independent, curiosity-driven research at the intersection of artificial intelligence and scientific discovery, within a collaborative industrial research lab that values academic-style innovation and publication.

The successful candidate will have the freedom to define and lead a research agenda aligned with MERL’s strategic interests in applying AI to challenging problems arising in industrial and scientific domains. This includes advancing foundational methods while demonstrating impact in real-world systems.

We are particularly interested in candidates working at the intersection of AI and scientific domains, including but not limited to:

AI for Mathematics and Scientific Computing

• AI-driven methods for optimization, numerical analysis, and large-scale scientific computing

• Learning-based approaches to modeling and analyzing complex dynamical systems

• Integration of machine learning with classical algorithms for improved efficiency and robustness

• Hypothesis formation, sequential experiment design, analysis and deductive discovery.

• Theorem development and proving, and algorithm discovery.

AI for Physical Sciences

• Physics-constrained or physics-informed AI models for understanding and designing material properties (e.g., optical, electrical, thermal)

• Data-driven and hybrid approaches for multi-scale modeling and simulation

• Differentiable simulators

• Discovery of emergent laws and governing equations in complex physical systems

• Foundational models for thermodynamics and electro-magnetics

AI for Earth and Environmental Sciences

• Methods for multi-scale environmental and geophysical systems

• Remote sensing and spatio-temporal modeling using satellite or sensor data

• Modeling, prediction, and decision-making for environmental and climate-related applications

Responsibilities for this position include:

• Define and pursue an independent research program in AI for Science, aligned with MERL’s research directions
• Develop novel machine learning and AI methodologies for scientific discovery, modeling, and design
• Collaborate with MERL researchers across disciplines to connect fundamental advances with industrial applications
• Publish research results in top-tier conferences and journals
• Contribute to the broader research community through open-source software, datasets, or other artifacts where appropriate

Qualifications for this position are:

• PhD in Computer Science, Applied Mathematics, Physics, Engineering, or a related field (or expected completion before start date)
• Strong background in machine learning, artificial intelligence, and computational science
• Experience in applying AI to scientific or engineering domains, particularly those domains described above
• Demonstrated ability to conduct independent research, as evidenced by a strong publication record in relevant venues
• Excellent communication skills and ability to collaborate in a multidisciplinary research environment

The pay range for this position at the commencement of employment is expected to be between $135,000 and $170,000 per year. Actual base pay will depend on a variety of individualized factors, including job-related knowledge, skills, and experience.

In addition to base salary, the total compensation package will include an annual performance-based bonus and a comprehensive benefits program encompassing medical, dental, and vision coverage; a generous 401(k) match; commuting and home office stipends and various paid time off programs (including vacation, sick time, personal and parental leave). Specific details regarding participation in these programs will be provided upon an offer of employment.

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.

PRINCIPALS ONLY. No phone calls please.

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

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.