PostDoc Researcher

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The CITY COLLEGE of NEW YORK

No

The AI-Enabled Bio-Inspired Materials discovery Ecosystem (AI-BIOME) at the CUNY City College of New York (CCNY) invites applications for Postdoctoral Researchers. Funded by the NSF grant award, AI-BIOME is a new, public-private Programmable Cloud Laboratory (PCL) Node dedicated to bio-derived, supramolecular, and bioinspired materials design, discovery, and characterization.

We are seeking exceptional, highly motivated early-career scientists to join our team at the frontier of artificial intelligence, robotics, and soft-matter physics. You will work directly with

• Lead PI/Science Lead Ronald Koder
• Co-PI/AI Lead Saptarashmi Bandyopadhyay
• Co-PI/Data Lead Raymond Tu

• Role:
  Post Doctoral Researchers
• Location:
  
  CCNY

This position offers a unique opportunity to work at the intersection of AI agent-enabled reasoning and hands‑on autonomous experimentation. Biological and bio‑inspired materials offer a massive, programmable design space perfectly suited for algorithmic generalization and optimization. You will help pioneer closed‑loop discovery, where multiple AI agents generate hypotheses, propose designs, autonomously plan and execute multi‑step trustworthy experiments with robots, and refine themselves in real time through scientific exploration.

• Research Integration:
  Conduct research integrating AI‑driven experimental design with automated materials synthesis and characterization, emphasizing trustworthiness, reliability, robustness, and transparency in AI decisions that guide embedded experimental workflows.
• Algorithms, Theory and System‑Level Research to Control AI Agents:
  Build robust and efficient algorithms to control AI Agents that can learn generalizable plans to design and synthesize bio‑inspired materials, adapt to mistakes in the plans autonomously, steer navigation and accelerate discovery and exploration at a distributed scale. This includes developing planning, reasoning, navigation and exploration algorithms (e.g., efficient RL, imitation learning approaches like behavioral cloning, game theoretic equilibriums, hierarchical controllers, causal and probabilistic reasoning modules) that ensure trustworthy behavior of agents in autonomous laboratory environments and enable long‑horizon, multi‑step high‑throughput experimental campaigns.
• Autonomous Workflow Development:
  Develop new workflows within the robotic platforms, focusing on training new capabilities to the robots. You will help design and validate autonomous laboratory protocols in which embedded AI agents coordinate liquid‑handling robots, robotic carts, analytical instruments, and cloud infrastructure in a closed loop high‑throughput experimentation environment.
• Scientific Publication and Communication:
  Disseminate scientific results to the broader community by publishing impactful research papers in reputed conferences and journals. Collaborate with PCL nodes jointly under the PCL research network.
• Mentorship:
  Supervise graduate research assistants, undergraduates and the workforce originating from the AI‑BIOME PCL.
• Collaboration:
  
  Work alongside our expansive network of partners, including researchers at Brookhaven National Laboratory, NVIDIA, Mozilla AI and other…