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Scientific Lead, Multi-omics

Remote / Online - Candidates ideally in
Dallas, Dallas County, Texas, 75215, USA
Listing for: American Heart Association
Full Time, Remote/Work from Home position
Listed on 2026-05-08
Job specializations:
  • Research/Development
    Clinical Research, Research Scientist
  • Healthcare
    Clinical Research
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below

Overview

Since our founding in 1924, we've cut cardiovascular disease deaths in half, but there is still so much more to do. To overcome today’s biggest health challenges and accelerate this progress, we need passionate individuals like you. Join our movement, be part of the progress, and help ensure a healthier future for all. You matter, and so does the impact you can make with us.

The American Heart Association has an excellent opportunity for a Scientific Lead, Multi-Omics
, working with the The Periodic Table of Food Initiative (PTFI)®. This position can be home-based.

This is a full-time, benefits-eligible, grant-funded opportunity. Funding will expire one year from the start date.

Responsibilities

The Scientific Lead, Multi-Omics drives demand for PTFI tools and data while leading laboratory expansion, enablement, and technical support across the global ecosystem. The role also contributes to analysis and translation of multi‑omics datasets including advancing clinically relevant thresholds to expand adoption and application of PTFI findings across research, clinical, and food system contexts.

Reporting to the Executive Director of Sustainable Food Systems @ Heart, this role provides scientific leadership to ensure scalable development and implementation of PTFI’s standardized multi‑omics methodologies for food composition analysis and food‑health research. The Scientific Lead supports growth of the PTFI laboratory network by identifying and onboarding high‑capacity laboratories, aligning training resources and analytical workflows, and guiding harmonized data generation and interpretation across the ecosystem to enable biomarker discovery, cross‑study comparability, and translation of molecular food composition data into biological and clinical insights.

Core

Responsibilities
  • Identify, assess, and engage high‑capacity analytical laboratories to join the PTFI global ecosystem.
  • Conduct technical evaluations of prospective institutions, including instrumentation, workflows, personnel capacity, and infrastructure.
  • Support scientific due diligence for laboratory partnerships, contracts, and agreements.
  • Strengthen adoption of standardized PTFI tools, protocols, and datasets across academic, nonprofit, healthcare, and industry partners.
  • Contribute to growing global demand for PTFI’s standardized multi‑omics tools and datasets through scientific partnerships and ecosystem engagement.
  • Serve as in‑house subject‑matter expert on multi‑omics methodologies for food biomolecular characterization and human biospecimen analysis.
  • Contribute to planning strategies for analytical method development including prioritization for method development of new and/or updated PTFI analytical platforms.
  • Provide scientific guidance on metabolomics and related omics platforms supporting food composition and translational food‑health research.
  • Guide harmonization of analytical workflows, quality control frameworks, and technical standards across participating laboratories.
  • Support integration of food composition data with human biological datasets in collaborative research contexts.
  • Contribute to analysis and interpretation of multi‑omics datasets to identify biomarkers and biologically meaningful patterns across foods and human biospecimens.
  • Work with the PTFI Lab Enablement Team to implement standardized tools and protocols across the laboratory network.
  • Provide technical guidance and troubleshooting support to ecosystem laboratories.
  • Coordinate with instrumentation vendors, software providers, and technical service partners to optimize analytical performance and capacity.
  • Partner with Food EDU to integrate training resources into lab enablement and workforce development.
  • Monitor adoption of standardized workflows and support reproducibility and quality improvement across laboratories.
  • Collaborate with data science and AI teams to ensure multi‑omics outputs are harmonized and interoperable across food and health datasets.
  • Support integration of laboratory outputs into PTFI databases, analytics tools, and translational platforms.
  • Contribute to workflows linking food composition data with human biomarker and clinical research
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