Fellow / and biology

Details

Title Fellow in AI/ML for Cellular and Protein Computational Biology

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 AI/ML and the ambition to develop new AI approaches for high-impact problems in cellular and protein computational biology.

This role focuses on applying modern AI/ML methods to protein and cellular biology, including protein structure prediction, protein-protein and small-molecule-protein docking, cell state prediction from large-scale Perturb-seq datasets, and multimodal modeling of protein function and cellular state.

We seek candidates with strong technical preparation in modern AI/ML, a demonstrated record of research accomplishment, and experience in computational biology or biological data analysis. Strong candidates may come from protein-focused, cell-state-focused, or multimodal biological modeling backgrounds and will have expertise in one or more of the following areas:

• foundation model training, evaluation, and adaptation

• protein structure modeling and docking

• cell state prediction from large-scale perturbation datasets

• multimodal modeling for protein function and cellular state prediction

• familiarity with AlphaFold, RFDiffusion, CellCap, or related models for protein and cellular biology

AI Fellows will work closely with one another and with Kempner faculty, researchers, and students on foundational machine learning and biologically informed scientific applications. The position is particularly well-suited to candidates eager to apply their technical expertise in modern AI to important problems in protein biology, cellular systems, 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 biology, bioengineering, biophysics, 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, RECOMB , ISMB , 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 protein structure modeling, protein-protein docking, or small-molecule-protein docking

• Experience with cell state modeling from large-scale perturbation datasets, including Perturb-seq or related data

• Experience with multimodal modeling for protein function or cellular state prediction

• Familiarity with models and methods relevant to protein and cellular biology, including AlphaFold, RFDiffusion, CellCap, or related systems

• Experience with large-scale datasets, distributed training, or high-performance computing environments

• Expertise in scientific applications of AI/ML in protein biology, cellular systems, and related areas of computational biology

Special Instructions

Please submit the following items in PDF format no later than 11:59pm EST Monday, June 1, 2026:

• CV.

• A research statement of no more than 2 pages describing your experience using modern AI/ML for protein structure, cellular state, or related biological modeling problems. Please be specific about your individual contributions.

• 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.

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 [email protected]

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

Keywords

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