Part-Time Assistant Programmer

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JOB DESCRIPTION AND POSITION REQUIREMENTS 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 ApplicantsBACKGROUND CHECKS/CLEARANCES Employment with the University will require successful completion of background check(s) in accordance with University policies.

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