NLP & Scientific Integrity Post-Doc

Position Overview 

NGRF (NovaGen Research Fund) is a new data science collaboration hub including multiple labs and centers. NGRF is seeking a researcher to join the LLM Lab and contribute to NGRF’s scientific discovery platform. This role combines original research in scientific integrity with hands-on development of NLP and AI capabilities on a large-scale biomedical data platform. 

The researcher will work with a multi-terabyte curated literature database, develop and evaluate NLP models, build retrieval-augmented generation (RAG) pipelines, and contribute to a federated knowledge graph that models scientific claims and evidence relationships. The role spans research and engineering — publishing peer-reviewed findings while building the models and pipelines that power NGRF’s platform. 

Key Responsibilities 

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  Scientific integrity research: Design and execute large-scale computational analyses of scientific publishing practices across the biomedical literature. Publish findings in peer-reviewed venues (e.g., Scientometrics, JASIST, Quantitative Science Studies). 

  
  


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  NLP model development: Develop and validate models for semantic analysis of scientific text — including claim extraction, relevance scoring, and relationship detection. Build on existing RAG infrastructure and vector search capabilities. 

  
  


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  Big data and pipeline engineering: Work with a multi-terabyte literature database and external APIs (PubMed, CrossRef, OpenAlex) to build scalable data processing and analysis pipelines. Integrate structured and unstructured data sources into reproducible workflows. 

  
  


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  Collaboration and outreach: Work with external partners in the research integrity community. Present findings at conferences and contribute to NGRF’s visibility in the scientific integrity space. 

  
  

Required Qualifications 

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  PhD in natural language processing, computational linguistics, computer science, information science, or a related field 

  
  


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  Publication record in NLP, text mining, or computational approaches to scientific literature 

  
  


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  Strong programming skills in Python with experience in modern ML/NLP frameworks (e.g., PyTorch, Hugging Face Transformers) 

  
  


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  Experience working with large text corpora and large-scale datasets 

  
  


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  Familiarity with vector databases, embeddings, semantic search, and retrieval-augmented generation (RAG) 

  
  


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  Experience with knowledge graphs, ontology design, or graph databases

  
  


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  Demonstrated ability to design and execute independent research projects 

  
  


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  Strong written and oral communication skills 

  
  

Preferred Qualifications 

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  Background in scientometrics, bibliometrics, or research integrity 

  
  


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  Experience with scientific publishing APIs and metadata (DOIs, PubMed, CrossRef, OpenAlex) 

  
  


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  Familiarity with claim extraction, relation extraction, or scientific argument mining

  
  


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  Proficiency with Git, GitHub, and collaborative software development workflows

  
  


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  Experience with Linux/Unix environments and command-line tools 

  
  


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  Familiarity with containerization (Docker) and CI/CD pipelines 

  
  


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  Experience with AI-assisted development tools (e.g., Claude Code, GitHub Copilot)

  
  


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  Experience deploying NLP models in production or near-production settings

  
  


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  Familiarity with Kubernetes, infrastructure-as-code, or cloud platforms (AWS)

  
  


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  Experience with SQL databases (PostgreSQL) and data modeling 

  
  


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  Track record of interdisciplinary collaboration

  
  

Compensation 

The prospective salary range for this position is $80,000–$92,000 annually.