Fellow in AI/ML for NeuroAI and Computational Neurobiology
Kempner Institute for the Study of Natural and Artificial Intelligence Fellow in AI/ML for NeuroAI and Computational Neurobiology
Summary
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
- Technical communication