Bioinformatics Scientist

Job description

Company Description Join us and make YOUR mark on the World! Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability. Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact. Job Description We have an opening for a Bioinformatics Scientist to conduct research, training, and evaluating next-generation bioinformatics and data management tools. As a member of our multidisciplinary team, you will collaborate with experts in artificial intelligence, machine learning, molecular biology, software engineering, and interface with experimentalists generating large datasets to explore opportunities to advance scientific capabilities in detection and surveillance of novel and emerging pathogens. This will include the development of new methods, tools, and algorithms for metagenomic sequence data analysis and pathogen characterization in addition to working with multiomic datasets and applying state of the art machine learning models for integrated data analysis and prediction. This position is in the Advanced Biotechnologies Integration group in the Biosciences and Biotechnology Division (BBTD). You will Analyze metagenomic datasets from environmental (e.g., wastewater, aerosol) and clinical (nasal swab, saliva, etc) samples to determine taxonomy and function. Research, develop, and implement computational and statistical techniques for analyzing novel and unknown sequences. Develop simulation-based and agentic tools for hypothesis generation and in silico testing. Contribute to biological data management such as metadata schemas, databases, data catalogs and integrated workflows. Contribute to and influence the development of innovative projects, principles, and ideas in biosurveillance and biodetection. Interact with technical contacts at sponsor and partner organizations routinely; represent the organization on specific technical projects. Determine, propose, and implement advanced analysis methodologies and contribute to identifying future research directions and proposals that will secure future projects in the field. Contribute to the completion of project milestones, balance multiple projects/tasks and priorities to ensure deadlines are met, working independently with minimal direction within the scope of assignments. Lead the development of manuscripts and presentations documenting project activities and research results. Oversee the activities of other personnel, providing informal mentoring and guidance to less experienced team members. Perform other duties as assigned. Qualifications Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship. Master’s degree in Computational Biology, Biophysics, Computational Bioengineering, Machine Learning, Statistics, Computer Science, Mathematics, or equivalent combination of education and related technical experience.. Significant experience in metagenomics, bacterial genomics, and next-generation sequencing (NGS) analysis. Advanced experience in scientific computing tools such as C/C++, Python, R, MATLAB, Nextflow, PostgreSQL, MySQL, MongoDB, and HPC schedulers. Significant experience developing and deploying end-to-end workflows for pathogen detection, taxonomic classification, genome assembly, subtyping, and metagenomic analysis. Proven ability to translate mission needs into scalable, reusable analytical frameworks and tools, with experience supporting both research and operational bioinformatics activities. Advanced experience in large data management such as metadata schema development, data cataloging, database development, and integration with pipelines, AI/ML models and workflows. Significant experience with high-performance computing, GPU programming, parallel programming, cloud computing, and/or running numerical simulations of complex workflows. Advanced verbal and written communication skills necessary to collaborate within a team environment and present technical information to varied audiences. Effective interpersonal skills and initiative necessary to interact with all levels of personnel and work independently in a collaborative, multidisciplinary team environment. Advanced ability to balance multiple projects, prioritize competing demands while maintaining high-quality standards, and provide guidance and informal mentoring to other personnel and junior team members. Ability to represent the organization as a primary technical contact and to contribute to the development of innovative projects, principles, and ideas. Qualifications We Desire PhD in Computational Biology, Biophysics, Computational Bioengineering, Machine Learning, Statistics, Computer Science, Mathematics, or a related field. Significant knowledge in gene calling, biological process modeling, or application of protein and genome language models sufficient to communicate effectively with team members and subject matter experts. Experience and advanced knowledge in developing and applying algorithms in advanced machine learning or cell modeling. Significant experience developing and implementing machine learning models such as deep learning, unsupervised feature learning, zero- or few-shot learning, active learning, transformer-based language modeling, multimodal learning. Pay Range $175,530 - $222,564 annually This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting; pay will not be below any applicable local minimum wage.  An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs. Additional Information #LI-Onsite All your information will be kept confidential according to EEO guidelines. Position Information This is a Career Indefinite position, open to Lab employees and external candidates. Why Lawrence Livermore National Laboratory? Included in 2026 Best Places to Work by Glassdoor! Flexible Benefits Package 401(k) Relocation Assistance Education Reimbursement Program Flexible schedules (*depending on project needs) Our values - visit https://www.llnl.gov/inclusion/our-values Security Clearance This position requires a Department of Energy (DOE) Q-level clearance. If you are selected, we will initiate a Federal background investigation to determine if you meet eligibility requirements for access to classified information or matter. Also, all L or Q cleared employees are subject to random drug testing. Q-level clearance requires U.S. citizenship. Pre-Employment Drug Test External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor. Wireless and Medical Devices Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession. This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices. If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas. Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings. 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