Predictive Microbial Genomics Postdoctoral Fellow (KBase Project)

Berkeley Lab's (LBNL) Environmental Genomics and Systems Biology (EGSB) Division has an opening for a Postdoctoral Fellow to join the US Department of Energy's (DOE) Systems Biology Knowledgebase (KBase) team! In this exciting role, you will help develop an iterative system that integrates data and findings into KBase, identify knowledge gaps, generate testable biological predictions, support experimental validation, and incorporate validated results back into the knowledge base. The position sits at the center of a system designed to continuously advance biological understanding. This position has an anticipated start date of November 1, 2026 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 benefits. Generous paid time off, sick time off, and holidays. A culture where you'll belong - we are invested in our teams! What You Will Do: Annotate, classify, and functionally analyze microbial genomes and pangenomes. Develop predictive models linking genotype to phenotype and gene function using the accrued KBase data corpus. Design prediction and validation cycles in collaboration with experimental researchers, and incorporate experimental results to improve subsequent predictions. Construct and refine genome-scale metabolic and microbial community models using data from the KBase corpus, including genome-wide fitness measurements, curated phenotypes, metabolic reconstructions, and other mechanistic information, for model training, conditioning, and retrieval. Develop and validate open benchmarks to evaluate model performance against biological mechanisms, including gene function, fitness, phenotype, and pathway completion. Define calibration and uncertainty measures that account for factors such as taxonomic distance, annotation quality, and data sparsity. Publish open, FAIR (findable, accessible, interoperable, and reusable), well-documented methods, code, benchmarks, and datasets, as well as scientific discoveries in peer-reviewed journals. What is Required: A recent Ph.D. (within the last 1-2 years) in Bioinformatics, Computational Biology, Microbiology, Systems Biology, or a related field. Demonstrated experience in the computational analysis of microbial genomes, including genome annotation, functional analysis, pangenomics, and phylogenomics. Proficiency in applying data science, machine learning, and statistical methods to biological data using Python and/or R. Strong organizational skills including experience maintaining detailed and accurate records of results and analyzed data. Excellent verbal and presentation skills including experience preparing research reports, manuscripts, and scientific publications for group meetings, conferences, and scientific journals. Demonstrated interpersonal communication skills including experience conducting independent, data-driven research and collaborating with an interdisciplinary research team. Desired Skills/Knowledge: Experience with genome-scale metabolic modeling, microbial community modeling, and/or physical Al applications in biology. Experience designing experiments or collaborating closely with wet-lab teams to validate computational predictions. Familiarity with high-performance and/or cloud computing, as well as reproducible workflow practices. Prior experience using KBase or comparable open biological data platforms. Additional Information: Appointment Type: This is a full time, exempt from overtime pay (monthly paid), 2 year (benefits eligible), Postdoctoral Fellow appointment with the possibility of renewal based upon satisfactory job performance, continuing availability of funds, and ongoing operational needs. You must have less than 3 years of paid postdoctoral experience. This position is represented by a union for collective bargaining purposes. Salary Range: The salary range for this position is $6,048 - $7,205 monthly / $72,576 - $87,000 annually and is expected to start at $6,048 monthly / $72,576 annually or above. Postdoctoral positions are paid on a step schedule per union contract and salaries are predetermined based on postdoctoral step rates. Each step represents one full year of completed post-Ph.D. postdoctoral and/or related research experience. 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 will be performed onsite at Lawrence Berkeley National Lab located at 1 Cyclotron Road, Berkeley, CA 94720. A REAL ID or other acceptable form of identification is required to access Berkeley Lab sites (for more information). 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, . #J-18808-Ljbffr Lawrence Berkeley National Laboratory