Postdoctoral Fellow in Agentic AI Science

Postdoctoral Fellow in Agentic AI for Science

Harvard John

A. Paulson School of Engineering and Applied Sciences

Professor Jia Liu is seeking a highly-motivated postdoctoral researcher with a strong background in agentic artificial intelligence and machine learning. The successful candidate will conduct independent, high-impact research at the intersection of autonomous AI systems, neural computation, omics and neurobehavior analysis.

The position focuses on developing AI agents inspired by and applied to complex biological systems, with an emphasis on autonomous reasoning, decision‑making, and reinforcement learning. The postdoctoral fellow will design, implement, and evaluate agentic AI frameworks that integrate computational bio/neuroscience principles with modern machine learning techniques.

Ph.D. in a relevant field (e.g., computer science, ML, computational neuroscience, bioengineering).

A strong research record demonstrated by publications in leading peer‑reviewed journals and conferences (e.g., NeurIPS, ICML, ICLR, Neuron, Nature Methods, or related venues) is preferred. The successful candidate should demonstrate these skills:

• Expertise in machine learning and AI, particularly LLM fine‑tuning and reinforcement learning
• Experience with multi‑agent systems or autonomous AI frameworks
• Solid foundation in computational biology
• Proficiency in Python and modern ML frameworks (e.g., PyTorch, JAX)
• Strong analytical, problem solving, and communication skills
• Ability to work independently and collaboratively in interdisciplinary research environments

Required application materials submitted through this site include 2‑3 recommendation letters, a statement of research interest, and a current CV.

Contact Email

$67,600 – $91,826

Pay offered to the selected candidate is dependent on factors such as rank, years of experience, training or qualification, field of scholarship, and accomplishments in the field.

Minimum Number of References

Required:

2

Maximum Number of References Allowed: 3

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