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

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

Company: Harvard University

Job Location: Cambridge, 02138

Category: Computer Science

Type: Full-Time

School: Faculty of Arts and Sciences

Department/Area: Kempner Institute for the Study of Natural and Artificial Intelligence

Position Description

The Kempner Institute at Harvard University seeks early-career researchers to help shape the future of AI as Kempner AI Fellows. We are looking for candidates with strong foundations in modern machine learning and the ambition 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 research accomplishment, 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, and adaptation
• agentic workflows, tool-using models, and AI systems
• bespoke scientific applications of AI/ML, including in the life sciences
• alternative architectures and systems-level approaches to modern AI

AI Fellows will work closely with one another and with Kempner faculty, researchers, and students on foundational machine learning and domain-informed scientific applications. The position is particularly well-suited to candidates eager to deepen their technical skills in foundation models and agentic systems while applying those methods to important scientific and technical problems.

Appointment Terms

• Fellows will conduct research under the direction of a Kempner Institute investigator.
• Fellows are appointed for a one-year term; reappointment may be possible for up to three consecutive years.
• Due to the importance of in-person mentoring, this position is based on campus, full-time, at Harvard University. Remote work for this position is not possible.

Basic Qualifications

• Bachelor's or master's degree in computer science, statistics, electrical engineering, applied mathematics, computational biology/neurobiology, or a related quantitative field required by the expected start date
• Strong technical background in modern AI/ML, including deep learning and hands-on experience with frameworks such as PyTorch or JAX
• Demonstrated research productivity, including publications in venues such as ICML, ICLR, NeurIPS, or similar, and/or substantial open-source research contributions
• 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-using models, 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 1, 2026:

1. CV.
2. A research statement of no more than 2 pages describing relevant experience in foundation models and AI systems, large-scale or distributed computing, and scientific applications of AI/ML, including the life sciences. Please be specific about your contributions to these projects.
3. References - 1-2 required
   • Please give the emails of up to 2 individuals who can describe your work and your potential for future discoveries.
   • Referees will be contacted to submit the letters directly to the Kempner Institute.
   • The application will not be considered complete until all letters have been received.
4. Transcripts (Undergraduate and/or Master's)

Candidates selected for further consideration will be asked to submit a short video presentation reviewing their past work; additional details will be provided at that stage. Following review of the videos, a subset of candidates will be invited to interview with members of the selection committee via Zoom.

Applications received after the deadline will be reviewed on a rolling basis if positions remain available.

We anticipate a start date of September 15, 2026.

Contact Information

Molly Marshall

Contact Email: KempnerInstitute@Harvard.edu

Salary Range

Expected annual salary is $54,600 for candidates holding a bachelor's degree and $60,060 for candidates holding a master's degree. Salary will be commensurate with qualifications and experience.

Minimum Number of References Required: 1

Maximum Number of References Allowed: 2