Postdoctoral AI Researcher in AI​/ML Foundation Models, Scientific , and AI Systems

Postdoctoral AI Researcher in AI/ML for Foundation Models, Scientific Applications, and AI Systems

Title
- Postdoctoral AI Researcher in AI/ML for Foundation Models, Scientific Applications, and AI Systems

School
- Faculty of Arts and Sciences

Department/Area
- Kempner Institute at Harvard University

Position Description
- The Kempner Institute at Harvard University seeks early-career researchers to help shape the future of AI as Postdoctoral AI Researchers. We are looking for candidates with deep expertise in modern machine learning and a strong record of research accomplishment who are excited to advance foundation models, agentic systems, and new AI approaches for high-impact scientific applications. We seek candidates with strong technical preparation in modern AI/ML, a demonstrated record of scholarly achievement, and an interest in contributing to ambitious research at the frontier of machine learning and science.

Areas of particular interest include: foundation model training, evaluation, scaling, and adaptation; agentic workflows, tool-augmented models, and AI systems; bespoke scientific applications of AI/ML, including the life sciences; alternative architectures and systems-level approaches to modern AI. Postdoctoral AI Researchers will work closely with Kempner faculty, researchers, and students on foundational machine learning and domain-informed scientific applications. These positions are especially well suited to candidates prepared to contribute to advanced research programs in modern AI while continuing to grow as scholars within a collaborative academic environment.

Candidates should be within 2 years of receiving their doctoral degree and will work under the direction of Kempner Institute faculty. Appointment Terms Postdoctoral AI Researchers conduct research under the general supervision of one or more Kempner faculty members. The appointment is for one year; reappointment may be possible for up to a total of three years, contingent on funding, project needs, satisfactory performance, and mutual interest.

This is a full-time, benefits-eligible postdoctoral appointment based at the Kempner Institute at Harvard University. Due to the importance of in-person mentoring and collaboration, this position is based on campus, full-time, at Harvard University. Remote work for this position is not possible.

Basic Qualifications
- PhD in computer science, statistics, electrical engineering, applied mathematics, computational biology, or a related quantitative field required by the expected start date. Candidates must have received their PhD on or after September 15, 2024, or be on track to complete all PhD requirements by the expected start date of October 15, 2026. Demonstrated expertise in modern AI/ML, including deep learning and hands-on experience with frameworks such as PyTorch or JAX.

Strong publication record in leading venues such as ICML, ICLR, NeurIPS, or comparable conferences and journals. Demonstrated experience implementing, training, evaluating, or fine-tuning modern machine learning models. Strong programming skills in Python and experience building and maintaining research code. Demonstrated ability to use modern AI-assisted and agentic coding tools effectively, such as Claude Code, Codex, or similar systems, in research and development workflows.

Ability to work effectively in a collaborative research environment and communicate technical work clearly.

Additional Qualifications
- Experience with foundation model training, post-training, adaptation, or evaluation Experience with agentic workflows, tool use, retrieval systems, or related AI systems Experience with large-scale datasets, distributed training, or high-performance computing environments Interest in scientific applications of AI/ML, including the life sciences Interest in alternative architectures and systems-level approaches to AI

Special Instructions
- Please submit the following items in PDF format no later than 11:59pm EST Monday, June 8, 2026: CV A research statement of no more than 2 pages describing your experience in foundation models, agentic systems, scientific applications of AI/ML, and/or systems-level…