Senior​/Principal R&D Biological Sciences and Engineering - AI​/ML-Driven Computational Biology

Overview

Job details:
Location Albuquerque, NM;
Full-Time;
Regular position.

Sandia National Laboratories is the nation's premier science and engineering lab for national security and technology innovation, with teams of specialists focused on cutting-edge work in a broad array of areas. World-changing technologies. Life-changing careers. Learn more about Sandia at: http://(Use the "Apply for this Job" box below).*

* These benefits vary by job classification.

Sandia National Laboratories invites exceptional candidates to join our world-class research team advancing the frontiers of AI-driven predictive biology and 'omics data integration. We are seeking a mid-career scientist passionate about applying artificial intelligence, machine learning, and computational modeling to uncover the principles governing living systems and their interactions with materials and the environment. This position offers the opportunity to develop next-generation tools that connect molecular to ecosystem scales - transforming complex biological data into predictive insight that enables design, control, and optimization of biological function in support of bioenergy, environmental resilience, and national security.

The successful candidate will help lead research that integrates cutting-edge AI frameworks with a variety of experimental data streams and high-performance computing to accelerate biological understanding, prediction, and design. Working within Sandia's collaborative environment, you will contribute to multidisciplinary projects funded by the DOE Office of Science Biological and Environmental Research (BER), the Alternative Fuels and Feed stocks Office (AFFO), the Joint Strategic Technology Office (JSTO), and other federal partners.

This role emphasizes the use of AI, data automation, and high-performance computing to accelerate discovery and advance predictive models of biological-environmental-material interactions.

On any given day, you may be called upon to:

• Work closely with experts across computational biology, materials science, and geoscience to design and build interoperable data infrastructures and model-integration workflows.
• Collaborate in the development and application of machine learning, AI, and multiscale modeling approaches to integrate and interpret complex 'omics datasets (genomics, transcriptomics, proteomics, metabolomics) and uncover hidden relationships across biological, environmental, and materials datasets.
• Lead the design of predictive models that connect biomolecular and microbial processes with geochemical and materials phenomena, including biomineralization, corrosion, and biofilm behavior.
• Partner with collaborators to test and validate model predictions.
• Publish and present high-impact research findings in leading journals, conferences, and DOE technical reports.
• Contribute to the mentorship of staff, postdoctoral researchers, and students in advanced computational and AI-driven biological analyses.

The selected applicant can work a combination of onsite and offsite work. The selected applicant must live within a reasonable distance for commuting to the assigned work location when necessary.

$117,500 - $235,700

* Salary range is estimated, and actual salary will be determined after consideration of the selected candidate's experience and qualifications, and application of any approved geographic salary differential.

• Bachelor s degree in a relevant discipline and five (5) years of directly relevant experience, or an equivalent combination of directly relevant education and engineering or scientific experience that demonstrates the knowledge, skills, and ability to perform independent research and development.
• Ability to obtain and maintain a DOE Q security clearance.

The ideal R&D S&E, Biological Sciences and Engineering candidate for Sandia National Laboratories will in addition possess the following:

• Graduate degree in Biology, Molecular Biology, Biochemistry, Biological Engineering, or a highly related field where an independent research project was a graduation requirement (e.g., independent project, thesis, or…