Fellow in AI/ML for NeuroAI and Computational Neurobiology at Kempner Institute for the Study of Natural and Artificial Intelligence – Harvard University | Jobyssey
Fellow in AI/ML for NeuroAI and Computational Neurobiology
Kempner Institute for the Study of Natural and Artificial Intelligence · Harvard University ·
Research fellow at Harvard's Kempner Institute applying modern AI/ML — deep learning with PyTorch or JAX in Python — to computational neurobiology. Day to day: developing brain foundation models and modeling neural activity and brain circuits from large-scale, multi-regional recordings under a Kempner investigator's direction.
You will conduct research under the direction of a Kempner Institute investigator. You will apply modern AI and machine-learning methods to computational neurobiology, neural activity, and brain circuits. You will help develop brain foundation models using large-scale, multi-regional recordings.
Responsibilities
Conduct research under the direction of a Kempner Institute investigator
Develop brain foundation models
Model neural activity and brain circuits from large-scale recordings
Apply AI/ML methods to neuroscience and computational biology
Requirements
Bachelor’s or master’s degree in a related quantitative field
Modern AI/ML
Deep learning
PyTorch or JAX
Research publications or substantial open-source research contributions
Machine learning model implementation, training, evaluation, or fine-tuning
Python
Research code maintenance
AI-assisted and agentic coding tools
Computational neurobiology, neural data analysis, or neural activity modeling