Data Science Fellow - AI/NLP

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Data ScienceData & AI

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Overview

(ID: 2026-2316) Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics,

Technical Tools

Data ScienceData & AI

(ID: 2026-2316)

What We Offer

~4 min read

✓100% Medical, Dental & Vision Coverage for Employees

✓Paid Time Off and Paid Holidays

✓401K match up to 5%

✓Educational Benefits for Career Growth

✓Employee Referral Bonus

✓Flexible Spending Accounts: Healthcare (FSA)

✓Parking Reimbursement Account (PRK)

✓Dependent Care Assistant Program (DCAP)

✓Transportation Reimbursement Account (TRN)

✓Design and implement AI/NLP methods for biomedical literature mining and structured protocol knowledge extraction.

✓Develop benchmark datasets, annotation guidelines, and evaluation pipelines for scientific information extraction.

✓Build and evaluate RAG, in-context learning, fine-tuning, graph matching, entity normalization, and KG query workflows.

✓Analyze extraction errors, model behavior, retrieval failures, grounding quality, and biological ambiguity.

✓Collaborate with software engineers to integrate research methods into usable tools and reproducible pipelines.

✓Collaborate with organoid biologists and domain experts to translate biological protocol knowledge into computable representations.

✓Prepare manuscripts, conference abstracts, technical reports, design documents, and open-source research artifacts.

✓Help define research milestones, evaluation criteria, and publication strategy for protocol intelligence work.

✓PhD in computer science, computational biology, bioinformatics, biomedical informatics, NLP, machine learning, data science, or a related field.

✓Strong Python programming skills.

✓Demonstrated research experience with NLP, information extraction, LLMs, RAG, transformers, structured prediction, or scientific text mining.

✓Ability to design controlled computational experiments, create benchmark datasets, and analyze results rigorously.

✓Familiarity with biological, biomedical, or scientific data.

✓Strong written communication skills and interest in publishing methods-oriented research.

✓Comfort working with complex, evolving research codebases and interdisciplinary teams.

✓Experience with scientific document processing, PDF parsing, biomedical literature mining, or methods-section extraction.

✓Experience with knowledge graphs, ontologies, graph databases, graph algorithms, or semantic data modeling.

✓Hands-on experience with fine-tuning LLMs, LoRA/QLoRA, Hugging Face, PyTorch, or API-based model evaluation.

✓Hands-on experience with prompt engineering, structured JSON extraction, schema validation, tool use, or agentic LLM workflows.

✓Hands-on experience with RAG systems, vector search, graph-augmented retrieval, or natural-language query over structured data.

✓Exposure to bioinformatics concepts (e.g., sequence alignment, clustering, or phylogenetic analysis) that can inform protocol comparison and similarity methods.

✓Background in stem cell biology, organoids, developmental biology, wet-lab protocols, or biological assays, enabling more effective collaboration with domain experts.