Job Description

The Artificial Intelligence and Machine Learning (AI/ML) Group in the Theory Division of the LLE is seeking an outstanding research scientist to advance AI/ML initiatives across the inertial confinement fusion (ICF) program. This role integrates rigorous scientific investigation and theoretical insight with expertise in AI/ML methods, translating these capabilities into practical impact in process optimization, diagnostic data analysis, agentic AI development, and data management. The successful candidate will make significant contributions to on-going efforts in optimization of material system fabrication processes, LLM-orchestrated agentic system development, and support efforts in physics-informed and PDE-based AI/ML code development.

Candidates must have strong experience in scientific AI/ML methods, differentiable programming, and experimental modeling, as well as solid programming skills in Python, PyTorch, JAX, or other AI/ML and differentiable programming languages. The ideal candidate will have expertise in one or more of the following areas: computational science and engineering, computer science, and materials science and process optimization.

RESPONSIBILITIES:

• Take a leading role in designing AI/ML frameworks to aid in process optimization and fabrication of high-quality optical materials and devices for high-power, high-energy laser systems
• Oversee the development of a secure, internal RAG-based chat service and scientific knowledge retention/recommendation system
• Contribute to the development and uncertainty estimation of AI emulators for physics-based codes used in ICF research
• Develop inverse design and real-time optimization capabilities using INNs, GNNs, neural operators, or other appropriate methods
• Collaborate with experimentalists and engineering staff to deploy scalable and real-time ML tools
• Publish research results in high-impact, peer-reviewed journals
• Serve as principal investigator or co-investigator on Genesis Mission and other research proposals
• Advise graduate and undergraduate students conducting AI/ML research

Qualifications

MINIMUM EDUCATION & EXPERIENCE:

• Ph D in machine learning, physics, computational physics, computer science, applied mathematics, or engineering
• Demonstrated proficiency in scientific computing with one or more of: Python, PyTorch, Julia, Jax, C++, Java or other modern computing languages
• At least five years of research experience in computational sciences, including a minimum of two years of postdoctoral experience at national laboratories or universities
• Strong written and oral communication skills
• Ability to work effectively, both independently and as part of a multidisciplinary team

Application Instructions

The applicant should submit:

• a cover letter;
• a curriculum vitae and a list of publications;
• at least two letters of recommendation

SALARY RANGE: $100,000 to $140,000

The referenced pay range represents the minimum and maximum compensation for this job. Individual annual salaries/hourly rates are set within the job's compensation range, and determined by considering factors including, but not limited to, market data, education, experience, qualifications, expertise of the individual, and internal equity considerations.

Equal Employment Opportunity Statement

EOE, including disability/protected veterans

The University of Rochester is committed to fostering, cultivating, and preserving an inclusive and welcoming culture to advance the University’s Mission to Learn, Discover, Heal, Create – and Make the World Ever Better. In support of our values and those of our society, the University is committed to not discriminating on the basis of age, color, disability, ethnicity, gender identity or expression, genetic information, marital status, military/veteran status, national origin, race, religion/creed, sex, sexual orientation, citizenship status, or any other characteristic protected by federal, state, or local law (Protected Classes). This commitment extends to non-discrimination in the administration of our policies, admissions, employment, access, and recruitment of candidates for all persons consistent with our values and based on applicable law.