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Lawrence Berkeley National Laboratory

Fundamental science enabling energy and environment

Metagenome Research Scientist

Environmental SciencesPosted on Nov 11
Full-timeBerkeley, CA, USA$82.9k - $132.6k /yr

About the Job

Requirements

  • A Ph.D. (or equivalent knowledge/training) in Bioinformatics, Computational Biology, Microbiology, Molecular Biology, Biochemistry, or a related discipline, and at least 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, including longitudinal and time-series data analysis, assembly, binning, metagenome-assembled genome 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 environments to analyze large-scale biological datasets.
  • 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.
  • Ability to develop and scale reproducible computational workflows such as 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.
  • Ability to develop solutions to complex problems while addressing research needs effectively and in a timely manner.
  • Ability to manage complex, multi-tiered projects with competing priorities while meeting milestones.
  • Oral, written, and presentation skills to communicate complex ecological and computational concepts effectively with internal and external staff, JGI users, and scientific collaborators.
  • Interpersonal communication skills and ability to collaborate across interdisciplinary teams, bridging ecological domain science with computational engineers, data scientists, and external biological research.

Responsibilities

  • Lead large-scale analyses of longitudinal metagenomic datasets, such as 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 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 use the Data Lakehouse, integrating time-series data, metagenome-assembled genome abundance profiles, and environmental metadata into predictive models of microbial function.
  • Provide scientific leadership for CSP and FICUS projects in collaboration 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 JGI in cross-institutional working groups and workshops focused on continental-scale ecology, time-series standards, and environmental microbiome dynamics.

Desired Qualifications

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

About the Company

Lawrence Berkeley National Laboratory

Fundamental science enabling energy and environment

Berkeley Lab is a national research facility that conducts unclassified basic science across many fields, funded by the U.S. Department of Energy and managed by the University of California. Its work aims to address energy and environmental challenges by using interdisciplinary teams and building advanced tools for scientific discovery. Researchers study biosciences, computing sciences, Earth and environmental sciences, energy sciences and technologies, and physical sciences. The lab hosts about 4,200 scientists, engineers, staff, and students on a 200-acre site near UC Berkeley, and it has earned many prestigious honors, including Nobel Prizes and national academy memberships. Its goal is to generate foundational science that leads to practical, transformational solutions for energy and environmental issues while training the next generation of scientists and engineers.

Company size
5,001-10,000
Company stage
Grant
Total funding
$2M
Headquarters
Berkeley, CA
Founded
1931

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