Help us build a focused, sharp system that turns peer-reviewed nutrition literature into transparent, evidence-based recommendations
Job Summary
Help us build a focused, sharp system that turns peer-reviewed nutrition literature into transparent, evidence-based recommendations.
You’ll implement the Extract, Transform Load (ETL) pipeline from OpenAlex, fine-tune and wire up transformer models for relation extraction, and ship a production-grade recommendation/generative layer backed by a provenance-rich knowledge graph.
Fully remote (U.S.); office space available at Penn State for hybrid/in-person if preferred.
Matching Summary
Help us build a focused, sharp system that turns peer-reviewed nutrition literature into transparent, evidence-based recommendations.
Salary
$57/hour; 20 hours/week; 50 weeks
Skills & Requirements
Must-have
Python 3.x
modern NLP/ML (PyTorch or TensorFlow, Hugging Face, scikit-learn)