Lead Software Developer - GPU-accelerated Energy Simulation and Machine Learning Methods

Lead Software Developer - GPU-accelerated Free Energy Simulation and Machine Learning Methods

Location:

Piscataway, NJ (Remote work possible with regular in‑person reporting)

Company:
Rutgers University, Laboratory for Biomolecular Simulation Research ((Use the "Apply for this Job" box below).) and Institute for Quantitative Biomedicine ()

• Design, implement, and optimize GPU‑accelerated software for alchemical free energy calculations and AI‑enhanced quantum mechanical force fields.
• Integrate new methods and performance optimizations into the next‑generation Amber software suite.
• Collaborate closely with Amber developers and the research team to implement new methods.
• Develop, test, and document software; perform simulations of ligand‑protein binding, analyze thermodynamic graphs, and maintain up‑to‑date knowledge of state‑of‑the‑art techniques.
• Prepare scientific manuscripts and proposals.

• PhD in biology (preferred) or chemistry and postdoctoral experience developing workflows using Amber.
• Proficiency in object‑oriented programming (Python, C++), GPU programming (CUDA), software engineering, design, and performance optimization.
• Experience with molecular simulation methods, particularly alchemical free energy and/or quantum/machine‑learning methods, and high‑performance computing.
• Deep familiarity with free energy workflows and Amber software.
• Strong written and oral communication skills in English.
• Ability to work independently and produce scientific manuscripts or proposals.

• Experience using integrated semi‑empirical density‑functional tight‑binding and deep‑learning neural networks.
• Experience with national production cyberinfrastructure resources.

Primarily office‑based computer work. Occasional travel for workshops and conferences. Remote work allowed with regular in‑person meetings.

• Medical, prescription drug, and dental coverage
• Paid vacation, holidays, and leave programs
• Retirement plans and voluntary tax‑deferred savings options
• Employee and dependent educational benefits (when applicable)
• Life insurance coverage
• Employee discount programs

It is University policy to provide equal employment opportunity to all its employees and applicants for employment regardless of their race, creed, color, national origin, age, ancestry, nationality, marital or domestic partnership or civil union status, sex, pregnancy, gender identity or expression, disability status, liability for military service, protected veteran status, affectional or sexual orientation, atypical cellular or blood trait, genetic information (including the refusal to submit to genetic testing), or any other category protected by law.

As an institution, we encourage all qualified applicants to apply. For additional information please see the Non-Discrimination Statement at the following web address: -statement