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Fellow in AI/ML for Cellular and Protein Computational Biology

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Summary

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.

You will conduct research under the direction of a Kempner Institute investigator. You will apply modern AI and machine-learning methods to protein structure, docking, cell-state prediction, and multimodal biological modeling. You will contribute to computational-biology research using large-scale biological data.

Responsibilities

  • Conduct research under the direction of a Kempner Institute investigator
  • Apply AI/ML methods to protein and cellular biology
  • Develop models for protein structure, docking, and cell-state prediction
  • Contribute to multimodal modeling of protein function and cellular state

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
  • Technical communication

Skills

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