Job Summary

This position will involve the design and development of novel AI methods, especially self-supervised learning techniques used for training large-scale foundation models, tailored for fundamental physics analyses. The successful candidate will have a strong interest in multidisciplinary and theoretical work, particularly across the areas of High-Energy Physics (HEP), astrophysics, cosmology, statistics, and machine learning. The candidate will work closely with Prof. Pettee, leading new research directions and supporting the cohesion and mentorship of the team.

The work schedule is flexible and will be determined at the time of hire. This position is in-person and eligible for a partially remote schedule.

Key Job Responsibilities

• Conducts literature reviews, prepares reports and materials, and disseminates information to appropriate entities
• Assists with the identification of research problems and the development of research methodologies and procedures
• Writes or assists in developing grant applications and proposals to secure research funding
• Attends and assists with the facilitation of scholarly events and presentations in support of continued professional development and the dissemination of research information
• Serves as a main point of contact and liaison with internal and external stakeholders providing information and representing the interests of a specialized research area
• Collects and analyzes research data, conducts experiments and interviews, and documents results according to established policies and procedures under general supervision and limited responsibility

Required Qualifications

• Strong interpersonal and communication skills
• Mentorship & leadership experience
• Demonstrated ability to lead independent, peer-reviewed research work at the intersection of AI and physics
• Fluency in at least one machine learning language (e.g. PyTorch)

Preferred Qualifications

• Research experience in projects that merge disciplines in fundamental physics
• Training and/or published research in theoretical physics
• Training and/or published research in data science & machine learning
• Domain expertise in high-energy physics and/or astrophysics

Education

PhD in physics or related fields (especially computer science, data science, statistics, applied math), required