Postdoc: ML for Physical Systems & Scientific Modeling

The Friedman School of Nutrition Science and Policy; Medford (MA); On-site; USD 61,000 - 74,000; Full time

Job summary

Tufts University’s Department of Electrical and Computer Engineering invites applications for a Postdoctoral Scholar in Machine Learning for Physical Systems. The role focuses on ML emulators or surrogate models for chaotic dynamics and materials modeling, with the PI and team shaping the research direction.

Responsibilities include independent and collaborative research, developing and validating ML models, disseminating results via publications and talks, and contributing to grant activity

Qualifications

• PhD in electrical and computer engineering, physics, applied mathematics, computer science, or related field.
• Strong research record and proficiency in scientific computing and ML frameworks.

Responsibilities

• Conduct independent and collaborative research on ML for physical systems.
• Develop and validate ML models and code for scientific problems.
• Disseminate results through publications and presentations.
• Contribute to grant activity and mentor student researchers.

Skills

Scientific computing

Modern ML frameworks

Education

PhD in related field

Job description

Tufts University’s Department of Electrical and Computer Engineering invites applications for a Postdoctoral Scholar in Machine Learning for Physical Systems. The role focuses on ML emulators or surrogate models for chaotic dynamics and materials modeling, with the PI and team shaping the research direction.

Responsibilities include independent and collaborative research, developing and validating ML models, disseminating results via publications and talks, and contributing to grant activity