Part-Time Assistant Programmer

Part-Time Programmer

The Department of Computer Science and Engineering within the College of Engineering is seeking applicants for a part-time programmer.

The role:

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 Open Alex, 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.

What you'll do:

• Stand up and own a Pub Med or Open Alex ETL that ingests open-access articles, normalizes metadata, and keeps our corpus fresh.
• Use and/or fine tune transformer models (e.g., BERT variants) to extract semantic triples (like: (ingredient)–[biolink:]–>(health condition)); build evaluation and error-analysis loops.
• Implement a ranking layer that blends evidence strength (study design, sample size, effect size) with model confidence.
• Build the recommendation/generative service that balances constraints (evidence score, compatibility, regulatory limits) and exposes a clean API.
• Construct/maintain a knowledge graph that links every recommendation back to source papers (full provenance) and supports plain-language evidence summaries.
• Collaborate tightly with PI and domain scientists; deliver milestones on a fast, 12-month pilot timeline.

Core stack we use (and you're comfortable with):

• Python 3.x; modern NLP/ML (PyTorch or Tensor Flow, Hugging Face, scikit-learn); data/ETL tooling (pandas, spaCy, Pydantic, Airflow/Prefect).
• APIs/services: RESTful design, auth, pagination, retries, structured logging, unit/integration tests, CI.
• Storage/search:
  Postgres + vector/embedding store; graph DB experience welcome.
• Dev Ops basics: containers, reproducible envs, simple local deploys, secrets management.

Nice to have:

• Deep NLP experience (relation extraction, weak supervision, prompt/adapter tuning).
• Semantic KGs (RDF/OWL, Neo4j/graph tooling), ontology work, and/or the Biolink Model.
• Experience with biomedical text corpora and literature mining.
• You've shipped scrappy, reliable research-to-prod systems before.

What you bring:

• 3+ years professional Python and ML/NLP engineering, or equivalent portfolio.
• Strong engineering hygiene (tests, docs, code review) and product sense.
• Clear, direct communication in a remote team.
• Bonus: prior work at the intersection of ML + biosciences/clinical data.

Logistics & pay:

• Fully remote (U.S.); office space available at Penn State for hybrid/in-person if preferred.
• Part-time at $57/hour, 20 hours/week, 50 weeks. Continuation beyond 50 weeks depends on renewal/next-round funding.
• Please submit a brief cover letter and resume/CV.
• For more information on restrictions for part-time remote employment locations:
  Notice to Out of State Applicants