Postdoc - AI-Driven Bio-Inspired Materials Discovery

Research Foundation of The City University of New York (RFCUNY); New York (NY); On-site; USD 55,000 - 65,000; Full time

Job summary

RFCUNY, through the AI-BIOME program at CCNY, seeks exceptional postdoctoral researchers to join a frontier project at the intersection of AI agent-enabled reasoning and autonomous experimentation. You will help build scalable, reproducible pipelines for design, synthesis, and characterization of bio-inspired materials.

Collaborate with lead researchers, supervise trainees, and work with partners across national labs and industry to advance closed-loop discovery and high-throughput workflows in

Qualifications

• Ph.D. in a relevant field.
• Experience with AI/ML for autonomous decision making including RL/Imitation learning.
• Hardware-software integration for robotic and automated systems.

Responsibilities

• Conduct research integrating AI-driven experimental design with automated materials synthesis and characterization, emphasizing trustworthiness, reliability, robustness, and transparency in AI decisions.
• Develop algorithms to control AI agents for design and synthesis of bio-inspired materials, including planning and high-throughput disciplines.
• Develop autonomous workflows coordinating robots, analytical instruments, and cloud infrastructure in closed-loop experimentation.
• Publish results and collaborate within the PCL network; supervise graduate students and undergraduates.

Skills

AI/ML algorithms

Reinforcement learning

Imitation learning

Game theory

Control algorithms

Autonomous decision making

Robotics

Education

Ph.D. in Computer Science or related field

Tools

Robotic platforms

Embedded systems

Cloud orchestration

Job description

RFCUNY, through the AI-BIOME program at CCNY, seeks exceptional postdoctoral researchers to join a frontier project at the intersection of AI agent-enabled reasoning and autonomous experimentation. You will help build scalable, reproducible pipelines for design, synthesis, and characterization of bio-inspired materials.

Collaborate with lead researchers, supervise trainees, and work with partners across national labs and industry to advance closed-loop discovery and high-throughput workflows in