Assistant Research Professor

Responsibilities

• Develop and apply multi-scale simulation frameworks for complex catalytic systems.
• Design and implement generalizable machine learning algorithms (e.g., graph neural networks) and large language models to accelerate and couple multi-scale simulations in catalysis.
• Lead and contribute to proposal development and manuscript preparation, including conducting comprehensive literature reviews and disseminating research outcomes.
• Present research findings at scientific meetings and conferences, and actively engage with the broader research community.
• Mentor and supervise graduate and undergraduate students, fostering a collaborative and productive research environment.
• Manage day-to-day laboratory operations and coordinate research activities within the group.
• Maintain and expand computational resources, including high-performance computing workflows and data infrastructure, to support ongoing research efforts.
• Perform additional related duties as assigned by the principal investigator.

Requirements

• Ph.D. in Chemical Engineering, Materials Science, Computer Science, Chemistry, Physics, or a closely related field.
• Strong background in multi-scale simulations.
• Proficiency in machine learning techniques, particularly in scientific applications.
• Demonstrated ability to work independently as well as collaboratively within a multidisciplinary team.
• Prior experience mentoring students and a track record of scholarly publications is desirable.

Compensation

Salary: $70,000.

Benefits

WPI’s benefits package includes a robust retirement match, wellness perks, tuition assistance and more!

Status

FLSA STATUS: United States of America (Exempt)

About the Role

The successful candidate will conduct cutting-edge computational research aimed at developing machine learning algorithms to enhance multi-scale simulations in catalysis. This work will contribute to next-generation technologies involving plasma catalysis, field-enhanced catalysis, electrocatalysis, and materials science. The position offers an exciting opportunity to work at the intersection of machine learning and kinetics in advanced catalytic processes.