Postdoc: Physics-Inspired Machine Learning

Syracuse University; City of Syracuse (NY); On-site; USD 62,000 - 65,000; Full time

Job summary

The Physics Department at Syracuse University invites applications for a Postdoctoral Researcher in machine learning and theoretical physics within Professor Alexander Maloney’s group.

The successful candidate will conduct machine learning research inspired by physics and collaborate with physicists and machine learning researchers at Syracuse as well as with researchers in the Simons Collaboration on the Physics of Learning.

Qualifications

• Ph.D. in Physics, Applied Mathematics, Computer Science, or related field
• Strong background in theoretical physics and/or machine learning techniques
• Experience in statistical physics, quantum field theory, quantum information, or related areas

Responsibilities

• Research in physics-inspired machine learning approaches
• Collaborate with physicists and machine learning researchers at Syracuse
• Collaborate with researchers in the Simons Collaboration on the Physics of Learning

Skills

Theoretical physics

Machine learning

Education

PhD in Physics or related field

Job description

The Physics Department at Syracuse University invites applications for a Postdoctoral Researcher in machine learning and theoretical physics within Professor Alexander Maloney’s group.

The successful candidate will conduct machine learning research inspired by physics and collaborate with physicists and machine learning researchers at Syracuse as well as with researchers in the Simons Collaboration on the Physics of Learning.