Fellow in AI/ML for NeuroAI and Computational Neurobiology

Position Description:

The Kempner Institute at Harvard University seeks early-career researchers to help shape the future of NeuroAI as Kempner AI Fellows. We are looking for candidates with strong foundations in modern machine learning and the ambition to build brain foundation models and other AI systems that advance our understanding of neural activity, brain circuits, and biologically grounded intelligence.

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 intersection of machine learning, neuroscience, and computational biology. This role centers on computational neurobiology and the use of modern AI/ML methods to model brain circuits and neural activity. In particular, fellows will help develop brain foundation models that predict patterns of neural activity from large-scale, multi-regional recordings.

We are especially interested in candidates with experience in computational neurobiology or neural data analysis, and expertise in one or more of the following areas:

• foundation model training, evaluation, and adaptation
• time-series modeling
• transformers, autoencoders, and dynamical systems models
• modeling brain circuits and neural activity from large-scale recordings
• large-scale scientific applications of AI/ML, including in the life sciences

AI Fellows will work closely with one another and with Kempner faculty, researchers, and students on foundational machine learning and neuroscience-informed scientific applications. The position is particularly well-suited to candidates eager to apply their technical expertise in foundation models to important questions in neuroscience and biological intelligence.

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 neuroscience, computational biology, neurobiology, physics, 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, COSYNE, CCN, 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
• Experience in computational neurobiology, neural data analysis, or modeling neural activity from large-scale recordings
• 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 time-series modeling
• Experience with transformers, autoencoders, dynamical systems models, or related approaches for sequential or neural data
• Experience modeling brain circuits and neural activity from large-scale, multi-regional recordings
• Experience with large-scale datasets, distributed training, or high-performance computing environments
• Expertise in neuroscience, biologically grounded intelligence, and scientific applications of AI/ML

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.