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A postdoctoral researcher at Harvard's Kempner Institute applies modern AI/ML methods, particularly deep learning in PyTorch or JAX, to computational neurobiology — modeling neural activity and brain circuits from large-scale recordings and helping develop brain foundation models.
A postdoctoral researcher at Harvard's Kempner Institute who advances foundation models, agentic workflows, tool-augmented models, and AI systems for high-impact scientific applications. Day to day: conduct ML research under Kempner faculty supervision, publish, and develop as an independent scholar using Python with PyTorch or JAX.
Research fellow at Harvard's Kempner Institute applying modern AI/ML — deep learning in PyTorch or JAX — to computational biology: protein structure and docking, cell-state prediction, and multimodal modeling of protein function and cellular state, working with large-scale biological data under a Kempner Institute investigator.
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.
Research fellow at Harvard's Kempner Institute conducting AI/ML research on foundation models, agentic workflows, and tool-using AI systems for scientific applications, including life sciences. Day to day: implementing, training, evaluating, and fine-tuning deep learning models in Python with PyTorch or JAX under a Kempner investigator's direction.
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