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Axle

Data Scientist Fellow — Multi-Omics Analysis

  • Seen live on Axle's site today
  • Senior
Pay
$90k to $100k a year USD
Location
Bethesda, MD
Open for
11 days
First seen
Oct 24, 2026
Apply on Axle's site (opens in a new tab)

Posting record

No flags

Open 11 days

The posting's record, oldest first
  1. Ghostless first sees this listing
  2. Last checked: still up
How we know

It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.

Ghostless records the day it first sees a posting, so a repost can't reset its age.

Last checked Nov 4, 2026.

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What the posting discloses

Pay
$90k to $100k a year USD
$90,000 — $100,000 USD (quoted from the posting)

Not stated: Real vacancy, AI screening.

Why these three

Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.

Skills mentioned

About the role

(ID: 2026-3889)

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)

Position Overview

The Bioinformatics Fellow for Multi-Omics Analysis will conduct comprehensive analyses of multi-omics data generated from organoid systems and corresponding normal tissues. The incumbent will characterize organoid fidelity, identify biomarkers of successful differentiation, and develop computational frameworks for organoid quality assessment, while gaining substantive training in integrative analysis of single-cell and multi-omics data. The work is central to the SOM Center’s research objectives, and the position is intended to prepare the Fellow for an independent research career in academia, government, or industry.

Key Responsibilities

  • Multi-omics analysis. Analyze complex datasets including single-cell RNA sequencing, bulk RNA sequencing, proteomics, and metabolomics data from a range of organoid systems and their tissue counterparts.
  • Pipeline development. Develop and implement computational pipelines for data processing, quality control, and statistical analysis, and document them so that analyses are reproducible across the Center.
  • Benchmarking. Integrate SOM-generated data with publicly available datasets in order to benchmark organoid characteristics against normal tissue profiles.
  • Method development. Develop and refine analytical approaches — including machine learning methods where appropriate — for classifying cellular states and assessing organoid quality, and contribute to standardized assessment protocols.
  • Collaboration and interpretation. Work closely with experimental teams to interpret results and guide protocol optimization, and collaborate with other computational staff on cross-modality data integration.
  • Dissemination. Contribute to manuscript preparation and present findings at scientific conferences.

•

Required Qualifications

  • Education. Doctoral degree (PhD) in bioinformatics, computational biology, biostatistics, or a related quantitative field, completed or anticipated prior to the start of the appointment.
  • Single-cell analysis. Extensive experience with single-cell data analysis, including familiarity with tools such as Seurat, Scanpy, or comparable platforms.
  • Programming. Strong programming proficiency in R and Python, together with experience in statistical analysis and data visualization.
  • Omics workflows. Working knowledge of proteomics and metabolomics data analysis workflows.

•

Preferred Qualifications

  • Prior experience analyzing organoid datasets.
  • Experience with machine learning approaches for biological data, familiarity with pathway analysis tools, and knowledge of developmental biology principles.
  • Experience with high-performance computing environments and version control systems.

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.

Salary Range

$90,000 — $100,000 USD

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