Metagenome Research Scientist

Berkeley Lab’s (LBNL) Joint Genome Institute (JGI) has an opening for a Metagenome Research Scientist to join the Metagenome Program!

In this exciting role, you will lead large-scale analyses of multi-year, multi-site metagenomic and metatranscriptomic time-series datasets, including NEON and MONet, to characterize microbial community dynamics and infer spatiotemporal interactions across ecosystems. You will have the opportunity to develop scalable bioinformatics workflows, leverage the JGI Data Lakehouse, formulate ecological hypotheses, and build predictive models of microbiomes across spatial and temporal gradients. A central deliverable will be standardized, reusable computational tools that enable JGI users to predict microbial interactions across ecosystems. Reporting to the Head of the Metagenome Program, this position will advance innovative analytical methods, interpret complex biological patterns, and support the Metagenome Program’s broader research and production activities.

The JGI is a global leader in genome science, helping shape the future of biological discovery through advanced genomic capabilities, expert support, and large-scale, AI-ready data resources. As a Department of Energy (DOE) Office of Science user facility supported by the Biological and Environmental Research (BER) program, JGI advances BER’s mission to achieve a predictive understanding of complex biological, Earth, and environmental systems in support of the nation’s energy and infrastructure security. Through world-class capabilities in genome sequencing, synthesis, transcriptomics, metabolomics, natural products, and data science, JGI supports cutting-edge research on plants, fungi, algae, microorganisms, and microbiomes. JGI is headquartered in Berkeley, CA at Berkeley Lab’s Integrative Genomics Building (IGB). To learn about more opportunities within JGI, click here.

This position has an anticipated start date of January 25, 2027.

We’re here for the same mission, to bring science solutions to the world. Join our team and YOU will play a supporting role in our goal to address global challenges! Have a high level of impact and work for an organization associated with 17 Nobel Prizes!

Why join Berkeley Lab?

We invest in our employees by offering a total rewards package you can count on:

• Exceptional health and retirement benefits, including pension or 401K-style plans
• A culture where you’ll belong - we are invested in our teams! 
• In addition to accruing vacation and sick time, we also have a Winter Holiday Shutdown every year.
• Parental bonding leave (for both mothers and fathers)
• Pet insurance 

What You Will Do:

• Lead large-scale analyses of longitudinal metagenomic datasets (e.g., NEON and MONet) to investigate microbial community assembly, succession, stability, and interactions across environmental gradients.
• Develop scientific directions, lead programmatic initiatives, support JGI users, and contribute to Metagenome Program production activities.
• Formulate and test ecological hypotheses and develop innovative, theory-driven analytical frameworks to understand spatiotemporal microbial interactions.
• Design, benchmark, and implement scalable computational methods and workflows for analyzing longitudinal metagenomic and metatranscriptomic data.
• Collaborate with JGI data scientists and computational teams to leverage the Data Lakehouse, integrating time-series data, MAG abundance profiles, and environmental metadata into predictive models of microbial function.
• Provide scientific leadership for CSP and FICUS projects, collaborating with JGI users, DOE BER investigators, NEON, EMSL, and external partners.
• Partner with JGI production, project management, IMG, and GOLD teams to operationalize research methods into standardized, reusable tools for the broader user community.
• Lead scientific publications and present findings at conferences, consortium meetings, and JGI user meetings.
• Supervise and develop team members, including recruitment, work direction, performance management, and professional development.
• Mentor and train postdoctoral researchers and technical staff in longitudinal metagenomics, ecological statistics, and data synthesis.

• Represent the JGI in cross-institutional working groups and workshops focused on continental-scale ecology, time-series standards, and environmental microbiome dynamics.

What We Are Looking For:

• A Ph.D. (or equivalent knowledge/training) in Bioinformatics, Computational Biology, Microbiology, Molecular Biology, Biochemistry or a related discipline and a minimum of 3 years of demonstrated expertise in Microbial Ecology or an equivalent combination of education and experience.
• Demonstrated experience analyzing complex metagenome, metatranscriptome, and genomic datasets, and longitudinal and time-series data analysis, assembly, binning and metagenome-assembled genome (MAG) generation, functional annotation, and taxonomic profiling.
• Demonstrated expertise in Microbial Ecology, including community assembly rules, niche differentiation, metabolic handoffs, spatiotemporal dynamics, and interaction network topology.
• Experience working in high-performance computing (HPC) environments to analyze large-scale biological datasets.
• Demonstrated proficiency with statistical programming and computational tools, such as Python, R, and UNIX/Linux environments, for advanced multivariate data analysis, time-series modeling, and visualization.
• Demonstrated ability to develop and scale reproducible computational workflows (e.g., WDL, Nextflow, and Snakemake) for large, multi-sample datasets.
• A strong record of impactful, peer-reviewed scientific publications demonstrating contributions to ecological hypothesis testing, microbiome analysis, or multi-omic data integration.
• Strong analytical skills, including the ability to develop creative solutions to complex problems, while addressing research needs in an effective and timely manner.
• Excellent organizational skills, including the ability to manage complex, multi-tiered projects with competing priorities, while meeting milestones.
• Demonstrated oral, written, and presentation skills including the ability to communicate complex ecological and computational concepts effectively with internal and external staff, JGI users, and scientific collaborators.
• Excellent interpersonal communication skills including collaborating effectively across interdisciplinary teams, bridging ecological domain science with computational engineers, data scientists, and external biological research.

Desired Qualifications:

• A Ph.D. in Bioinformatics, Computational Biology, Microbiology, Molecular Biology, Biochemistry or a related discipline.
• Familiarity with continental-scale environmental monitoring programs (e.g., NEON, MONet) or longitudinal soil and aquatic microbiome datasets.
• Experience applying machine learning, network inference, dynamic systems modeling, or predictive modeling to investigate microbial interactions.
• Demonstrated ability to effectively supervise staff, including assigning work, providing coaching and performance feedback, and supporting employee development.

Additional Information:

• Application Date: Priority consideration will be given to candidates who apply with a curriculum vitae (CV) or resume and a cover letter describing their interest in this position by December 4, 2026. Applications will be accepted until the job posting is removed.

• Appointment Type: This is a full time, exempt from overtime pay (monthly paid), 2 year (benefits eligible), Career Track Term appointment with the possibility of extension or conversion to Career appointment based upon satisfactory job performance, continuing availability of funds, and ongoing operational needs.
• Union Represented: This position is represented by a union for collective bargaining purposes.

• Salary Information: This position has a budgeted salary range of $82,860 - $132,588 annually for job code S06.1. It is not typical for an individual to be offered a salary at or near the top of the range for a position. Salary will be commensurate with the final candidate’s qualification and experience, including skills, knowledge, relevant education, certifications, and aligned with the internal peer group (if applicable, and union contract agreement).
• Background Check: This position is subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
• Work Modality: This position is eligible for a hybrid work schedule - a combination of teleworking and performing work onsite at Lawrence Berkeley National Lab, located at 1 Cyclotron Road, Berkeley, CA 94720. A minimum of 2 onsite days per week is required. Work schedules are dependent on business needs. Individuals working a hybrid schedule must reside within 150 miles of Berkeley Lab. A REAL ID or other acceptable form of identification is required to access Berkeley Lab sites (for more information click here).

Want to learn more about working at Berkeley Lab? Please visit: careers.lbl.gov

Equal Employment Opportunity Employer: The foundation of Berkeley Lab is our Stewardship Values: Team Science, Service, Trust, Innovation, and Respect; and we strive to build community with these shared values and commitments. Berkeley Lab is an Equal Opportunity Employer. We heartily welcome applications from all who could contribute to the Lab's mission of leading scientific discovery, excellence, and professionalism. In support of our rich global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories under State and Federal law.

Misconduct Disclosure Requirement: As a condition of employment, the final candidate who accepts an offer of employment will be required to disclose if they have been subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct; or have filed an appeal of a finding of substantiated misconduct with a previous employer. For additional information, click here.