School: Faculty of Arts and Sciences

Position Description:

• 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
  
  

• 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 neuroscience, computational biology, neurobiology, physics, 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, COSYNE, CCN, or comparable conferences and journals, 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:

• Expertise in neuroscience, biologically grounded intelligence, and scientific applications of AI/ML.
• 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.
• 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.
• Interest in alternative architectures and systems-level approaches to AI
  
  

Contact Information:

Contact Email: KempnerInstitute@Harvard.edu

Equal Opportunity Employer:

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions or any other characteristic protected by law.

Salary Range:

About Harvard University

Harvard University is devoted to excellence in teaching, learning, and research, and to developing leaders in many disciplines who make a difference globally. The University, which is based in Cambridge and Boston, Massachusetts, has an enrollment of over 20,000 degree candidates, including undergraduate, graduate, and professional students. Harvard has more than 360,000 alumni around the world. The University has twelve degree-granting Schools in addition to the Radcliffe Institute for Advanced Study, offering a truly global education. Established in 1636, Harvard is the oldest institution of higher education in the United States.

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