PostDoc Researcher

Thank you for considering a career with the Research Foundation of The City University of New York (RFCUNY). The team at RFCUNY is made up of dedicated, talented professionals committed to providing the services that allow CUNY researchers, faculty, and staff to focus on their intellectual curiosity and scientific discoveries. We are pleased that you are interested in exploring opportunities to join RFCUNY. Primary Location: The CITY COLLEGE of NEW YORK Position at a Glance Role: PostDoctoral Researchers Location: CCNY Role 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. Key Responsibilities 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 collaborators in major National Labs and companies. Other duties as assigned. Qualifications Ph.D. in Computer Science, Machine Learning, Robotics, Electrical and Computer Engineering, Computational Materials Science, Chemical Engineering, Computational Physics, Bioengineering, Computational Chemistry, or a related discipline. Experience or strong interest in developing AI/ML algorithms and methods for Single‑Agent and Multi‑Agent Autonomous Decision Making (such as reinforcement learning, imitation learning, game theory, control algorithms, large multimodal models (VLMs/VLAs), or Bayesian optimization) to autonomously explore physical scientific discovery, laboratory automation, or experimental control. Experience or strong interest in hardware development, focusing on building complete hardware‑software systems to accelerate discovery in material and interfacial science, including robotic platforms, embedded chemical engineering systems and automated analytical pipelines tightly integrated with AI agents and cloud‑based orchestration. Ability to work independently while contributing effectively to a highly collaborative, multidisciplinary team environment. A strong commitment to responsible research practices, reproducibility, research ethics and clear communication of autonomous behavior in scientific settings is expected. Work Arrangement Work Arrangement: On‑Site at the CCNY campus in the West Harlem Innovation Triangle, with close coordination in CUNY GC and CUNY ASRC. Appointment Period: One year, starting October 1, 2026. Appointment Type: Full‑time (Renewable based on performance / funding). Our Environment: AI‑BIOME is co‑located within the CUNY City College of New York (CCNY) and CUNY Advanced Science Research Center (ASRC) in New York City and is the only PCL node in the New York, New Jersey, Connecticut Metropolitan Area. You will have access to unmatched computing infrastructure, high‑throughput liquid‑handling robotics, and automated analytical tools (including photoelectron & Raman spectroscopies, AFM, and electron microscopy). AI‑BIOME’s programmable cloud laboratory environment is designed for AI agents‑enabled scientific discovery in autonomous laboratories, where AI agents make autonomous decisions based on computational models with robotic execution for high‑throughput experimentation in a unified platform. AI‑BIOME will serve as a national training hub, providing fellows with strong intellectual and career‑development support. Pay and Benefits Pay Range: $55,000 to $65,000 RFCUNY Benefits RFCUNY Employee Benefits and Accruals Equal Employment Opportunity Statement The Research Foundation of the City University of New York is an Equal Opportunity/Affirmative Action/Americans with Disabilities Act/E-Verify Employer. It is the policy of the Research Foundation of CUNY to provide equal employment opportunities free of discrimination based on race, color, age, religion, sex, pregnancy, childbirth, national origin, disability, marital status, veteran status, sexual orientation, gender identity, genetic information, marital status, domestic violence victim status, arrest record, criminal conviction history, or any other protected characteristic under applicable law. RFCUNY Overview The Research Foundation of The City University of New York (RFCUNY) is a nonprofit educational corporation founded in 1963 to provide post‑award fiscal and administrative support for CUNY’s research and sponsored programs. RFCUNY’s services allow CUNY researchers, faculty, and staff to focus on their intellectual curiosity and scientific discoveries, on projects and programs that serve our local and global communities, proposing concrete solutions to society’s most pressing challenges. RFCUNY serves as a fiscal agent and works closely with all the CUNY campus Grants Offices to perform the core functions of post‑award financial management for CUNY research projects and sponsored programs. These functions include legal assessment and signing of agreements where RFCUNY is named as a fiscal agent; setting up award accounts; preparing sub‑awards and assisting PIs in monitoring the work of the recipients of sub‑awards; supporting project directors with hiring and managing research project and sponsored program staff; supporting the purchasing and paying for goods and services with grant and program funds; managing financial aspects of projects including accounts receivable, financial reporting, invoicing, budget monitoring, and cost compliance with uniform guidance; ensuring that sponsor financial requirements are met; monitoring compliance with applicable project and financial management rules and laws; supporting the management of independent and external audits and financial reviews; and providing data, information, management expertise, and other supports to CUNY’s research and sponsored programs. #J-18808-Ljbffr