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Full Time Data Science Postdoc Jobs in Washington, DC

The postdoc will work at the intersection of large language models, biomedical NLP, scientific ... Data Science Fellow - AI/NLP To be considered for this position, please upload a document as your ...

Minimal ( Job Type: Full-Time Clearance: Active Top Secret (TS) with ability to obtain SCI Job Posting Estimated Close Date: July 30, 2026 Overview: INTECON is seeking a Senior Data Science ...

Minimal ( Job Type: Full-Time Clearance: Active Top Secret (TS) with ability to obtain SCI Job Posting Estimated Close Date: July 30, 2026 Overview: INTECON is seeking a Senior Data Science ...

Minimal ( Job Type: Full-Time Clearance: Active Top Secret (TS) with ability to obtain SCI Job Posting Estimated Close Date: July 30, 2026 Overview: INTECON is seeking a Senior Data Science ...

Eligible for Employee Referral Program The minimum and maximum full-time annual salaries for this ... McLean, VA * $170,872.00 - $267,900.00 for Manager, Data Science Candidates hired to work in other ...

Eligible for Employee Referral Program The minimum and maximum full-time annual salaries for this ... McLean, VA * $170,872.00 - $267,900.00 for Manager, Data Science Candidates hired to work in other ...

Data Science Consultant Location * Washington, DC Area (Hybrid) Summit is a specialized analytics ... Full-time employees are eligible for: * Medical, dental, and vision insurance * Health Savings ...

Data Science Consultant Location * Washington, DC Area (Hybrid) Summit is a specialized analytics ... Full-time employees are eligible for: * Medical, dental, and vision insurance * Health Savings ...

Stay current with emerging data science techniques, tools, and technologies Do you have what it ... UNAVAILABLEEmployment Type: FULL_TIME

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Showing results 1-20

Full Time Data Science Postdoc information

See Washington, DC salary details

$65.1K

$77.1K

$146.1K

How much do full time data science postdoc jobs pay per year?

As of Jul 30, 2026, the average yearly pay for full time data science postdoc in Washington, DC is $77,061.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,800.00 and $67,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Full Time Data Science Postdoc, and why are they important?

To excel as a Full Time Data Science Postdoc, you need an advanced degree (usually a PhD) in a quantitative field, strong statistical analysis skills, and experience in research methodologies. Proficiency with programming languages such as Python or R, data analysis libraries, and tools like TensorFlow or SQL is typically required. Exceptional problem-solving ability, clear communication, and collaborative skills help you stand out in multidisciplinary research environments. These competencies are essential for generating impactful research outcomes, advancing scientific knowledge, and effectively sharing results with both technical and non-technical audiences.

What is a Full Time Data Science Postdoc?

A Full Time Data Science Postdoc is a postdoctoral research position focused on applying advanced data analysis, statistical modeling, and machine learning methods to solve complex problems in academic, industrial, or research settings. These positions are typically held by individuals who have recently completed a PhD in fields such as computer science, statistics, mathematics, or related disciplines. The role often involves working on large datasets, developing new algorithms, publishing research findings, and collaborating with interdisciplinary teams. Full-time postdocs are expected to dedicate their working hours entirely to research and related academic activities. This experience often serves as a bridge to permanent positions in academia or industry.

What are the typical collaboration opportunities for a Full Time Data Science Postdoc within a research institution or industry team?

As a Full Time Data Science Postdoc, you can expect to work closely with multidisciplinary teams that may include data engineers, domain experts, software developers, and senior researchers. Collaboration often involves joint problem-solving, co-authoring publications, and contributing to grant proposals or product development. You'll likely participate in regular meetings, data reviews, and brainstorming sessions, which provide valuable opportunities to expand your professional network and learn from colleagues in different fields. These collaborative experiences are not only essential for project success but also enhance your skills and visibility for future career advancement.
What are popular job titles related to Full Time Data Science Postdoc jobs in Washington, DC? For Full Time Data Science Postdoc jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Full Time Data Science Postdoc jobs in Washington, DC look for? The top searched job categories for Full Time Data Science Postdoc jobs in Washington, DC are:

Data Science Fellow - AI/NLP

Axle

Rockville, MD

Full-time

Re-posted 20 days ago


Job description

(ID: 2026-2316)

Axle 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 nationally and abroad. 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 some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).

Benefits We Offer:

  • 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)

We are seeking a postdoctoral researcher to develop AI/NLP and knowledge engineering methods that transform biomedical literature, experimental protocols, and source evidence into structured, quarriable, and evidence-grounded knowledge for organoid protocol standardization and optimization.

The postdoc will work at the intersection of large language models, biomedical NLP, scientific document understanding, knowledge graphs, ontology grounding, computational biology, and human-in-the-loop curation. Potential projects include LLM-based protocol extraction, retrieval-augmented literature mining, curated knowledge graph construction, ontology and entity normalization, protocol comparison, consensus protocol derivation, benchmark design, and natural-language interfaces over structured biological knowledge.

Cover Letter Required — Please Answer the Following Questions and Submit Application at: Data Science Fellow - AI/NLP
To be considered for this position, please upload a document as your Cover Letter that answers the six questions below. Applications submitted without this document will not be considered.

  1. What experience do you have working with large datasets and compute clusters?
  2. Describe your experience building workflows/pipelines and/or using bioinformatics software and tools to analyze data.
  3. What programming languages are you comfortable using for bioinformatics data analysis?
  4. What bioinformatics areas are you familiar with? (e.g., single cell, bulk genomics, transcriptomics, epigenetics, flow, spatial, metagenomics, etc.)
  5. What life science disciplines do you have experience in? (e.g., immunology, infectious disease, cancer research, etc.)
  6. Provide examples of basic machine learning/AI concepts and/or how you've applied them in bioinformatics data analysis.

Responsibilities

  • 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.

Required Qualifications

  • 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.

Preferred Qualifications

  • 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.

Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.

The diversity of Axle's employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.

Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate's experience, qualifications, skills, and location.

#IND

Salary Range
$90,000—$100,000 USD