NLP & Scientific Reasoning Post-Doc

Responsibilities

• 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).
• 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.
• 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.
• 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
• PhD in natural language processing, computational linguistics, computer science, information science, or a related field
• Publication record in NLP, text mining, or computational approaches to scientific literature
• Strong programming skills in Python with experience in modern ML/NLP frameworks (e.g., PyTorch, Hugging Face Transformers)
• Experience working with large text corpora and large-scale datasets
• Familiarity with vector databases, embeddings, semantic search, and retrieval-augmented generation (RAG)
• Experience with knowledge graphs, ontology design, or graph databases
• Demonstrated ability to design and execute independent research projects
• Strong written and oral communication skills

Requirements

• Background in scientometrics, bibliometrics, or research integrity
• Experience with scientific publishing APIs and metadata (DOIs, PubMed, CrossRef, OpenAlex)
• Familiarity with claim extraction, relation extraction, or scientific argument mining
• Proficiency with Git, GitHub, and collaborative software development workflows
• Experience with Linux/Unix environments and command-line tools
• Familiarity with containerization (Docker) and CI/CD pipelines
• Experience with AI-assisted development tools (e.g., Claude Code, GitHub Copilot)
• Experience deploying NLP models in production or near-production settings
• Familiarity with Kubernetes, infrastructure-as-code, or cloud platforms (AWS)
• Experience with SQL databases (PostgreSQL) and data modeling
• Track record of interdisciplinary collaboration

Benefits

Additional Information

(ID: 2026-1886) Axle Informatics is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations around the globe. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with premier research organizations and facilities including multiple institutes at the National Institutes of Health (NIH) and other public and private organizations. Benefits We Offer: 100% Medical, Dental & Vision Coverage for Employees Educational Benefits for Career Growth Paid Time Off (Including Holidays) Employee Referral Bonus 401K Matching Flexible Spending Accounts: Healthcare (FSA) Parking Reimbursement Account (PRK) Dependent Care Assistant Program (DCAP) Transportation Reimbursement Account (TRN) Position Overview 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.

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