Bioinformatics Programmer 5 (5993U), Innovative Genomics Institute - 46618
University of California Berkeley
Location: Berkeley, California
Internal Number: 3709102
Bioinformatics Programmer 5 (5993U), Innovative Genomics Institute - 46618
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We are looking for equity-minded applicants who represent the full diversity of California and who demonstrate a sensitivity to and understanding of the diverse academic, socioeconomic, cultural, disability, gender identity, sexual orientation, and ethnic backgrounds present in our community. When you join the team at Berkeley, you can expect to be part of an inclusive, innovative and equity-focused community that approaches higher education as a matter of social justice that requires broad collaboration among faculty, staff, students and community partners. In deciding whether to apply for a position at Berkeley, you are strongly encouraged to consider whether your values align with our Guiding Values and Principles, our Principles of Community, and our Strategic Plan.
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The Innovative Genomics Institute (IGI) is a non-profit, academic research organization formed through the partnership of UC Berkeley and UC San Francisco, and located on the UC Berkeley campus. A key focus of the IGI is accelerating translation of CRISPR-based approaches to address real-world problems in human health, agriculture, and climate.
The IGI is committed to hiring and developing staff who want to work in a high-performing culture that supports the outstanding work of our faculty and students. The IGI is interested in candidates who will contribute to our commitment to excellence, diversity, and inclusion in academia. The IGI is also interested in applicants who may have had non-traditional career paths, taken time off for family/personal reasons, or excelled in careers outside academia. Most of our job postings list 'required' and 'preferred' qualifications. We encourage individuals to apply who do not meet every preferred qualification, but who could grow and thrive in the role.
Application Review Date
The First Review Date for this job is: December 22, 2022
Deploys and integrates large-scale cluster computing, storage, and network infrastructure.
The group and institute rely on the turnaround of large-scale sequencing data to biologically relevant results in an extremely rapid way.
This requires a large-scale computing system that integrates multiple compute servers into a single accessible compute cluster system. The Bioinformatics Programmer applies an advanced understanding of Linux, x86, and cluster systems.
Manages and scales high-speed network infrastructure.
Manages complete usage of group computing infrastructure by testing for inefficiencies.
Monitors software being utilized in existing and new pipelines are properly configured to take advantage of highly distributed computing resources.
Ensures that group members' bioinformatic software and pipelines are properly configured and deployed to take full advantage of computing infrastructure.
Resolves problems with computing hardware and software.
Fixes high-end cluster computing infrastructure software and hardware failures.
Rapidly identifies problems with compute infrastructure in a heterogeneous environment, ranging from small to large sized compute nodes.
This includes being able to troubleshoot hardware system failures and network failures.
Distinguishes between true hardware failures from software and/or usage failures by the group.
Responsible for direct hands-on repair of computing infrastructure and solving technical computing problems independently.
Perform independent and group research with the goal of novel biological discoveries.
Develops methods that incorporate both biological and computational knowledge to facilitate the discovery of new biological entities that may include the discovery of novel viruses and mobile genetic elements; the discovery of new metabolic and energetic pathways using both existing and novel tools.
Central to this is the facilitation of methods for the discovery of new genome editing tools.
Analyzes and synthesizes different types of data (chemical, physical, and biological) from many different environments (soil, marine, deep subsurface).
Focuses on the main research goals for the group that includes the integration of different types of data from many disparate environments.
Utilizes modern data science tools to integrate large sequencing datasets with heterogeneous data types. Specifically, the coordination of microbial and viral genomes with biologically relevant data.
For example, the association between microbial genomes and the correspondence of microbial genomes with environmental parameters (for example - sulfur and nitrogen species concentrations).
Authors manuscripts for publication in research journals; present oral and poster presentations at research conferences.
Authors scientific level publications in high-level journals.
Responsible for quality graphics and figures from complex scientific data.
As needed, collaborates with other members of the group and non-group collaborators with publications and presentations.
Develops new algorithms and bioinformatic processing pipelines for genome reconstruction and analysis from massive metagenomic and metatranscriptomics.
Creates bioinformatic algorithmic and processing pipelines in order to scale to massive dataset sizes.
Develops bioinformatic methods so they can be broadly applicable to data from different environmental sources and sequencing platforms.
For example, development tools must be able to process from both complex and simple communities and data from both long and short-read sequencing platforms.
Creates Bioinformatic pipelines in order to be deployed across heterogeneous computing systems and be disseminated for use by users not part of the group.
Guides institute members in the selection of appropriate bioinformatic analyses.
Assists members of the group with analysis methods applying various data types and analyses.
These data types range from single gene surveys to complex metagenomic and metatranscriptomic large sequencing datasets.
The analysis includes the selection of pipelines that will effectively take advantage of compute infrastructure while maintaining data and analysis integrity.
Applies advanced statistical knowledge of the analysis of microbial communities that includes the selection of correct wet lab and field protocols that will affect downstream bioinformatic method selection and analyses.
Train staff, graduate students, and postdoctoral researchers in directly performing bioinformatic programming development.
Utilizes both direct one-on-one and group interactions with members of the group with varying degrees of bioinformatic expertise.
Directly communicates and trains group members that are primarily biologists that have varying degrees of experience in computational systems and bioinformatic understanding.
Develops and implements strategies with executive personnel for computational biological programs for large research groups, departments, and institutes.
Manages data access and priorities for members of the group and international collaborators.
The availability of the computational resources of the group is generally limited.
As a result, one of the main goals is to ensure that computational infrastructure, specifically data storage, is properly balanced between archival and contemporary data sources.
Additionally, monitors data access as the bulk of the computational resources are meant for group members.
Collaborates with outside members and takes precautions in securing data to ensure that members and collaborators do not improperly use data.
This also extends to computational resource usage, as collaboration is essential to the group, but must not hinder internal group usage.
Verifies the quality, standardization, and providence of new data.
Monitors large amounts of novel sequencing data that is constantly being generated.
The new data entering the lab must be processed in a way that is both standardized and usable by the whole group.
Develops practices and methods that ensure that all incoming data to the lab conforms to robust and standardized quality control.
Process new data in a way that is translatable to a large multi-user group with varying degrees of technical training.
This can mean ensuring that new data is tagged in a way that is understandable by everyone in the lab to ensure that data processing pipelines are compatible with existing analysis infrastructure.
In collaboration with development partners and IGI leadership, participates in the development of proposals and funding requests.
Leads a team of bioinformatics programming professionals.
Responsible for project budgets and financial reporting.
Expert knowledge of bioinformatics methods, applications programming, web development, and data structures.
Expert understanding of relational databases, web interfaces, and operating systems.
Highly developed project management skills.
Expert knowledge of modern biology and applicable field of research.
Highly developed interpersonal skills in order to work with both technical and non-technical personnel at all levels internally and externally to the organization, including the ability to effectively communicate and interface with the campus, departmental, and institute leadership.
Communication skills to work with both technical and non-technical personnel in multiple fields of expertise and at various levels including the ability to guide both bioinformatic and non-bioinformatic researchers.
Ability to effectively communicate and interface with the campus, departmental, and institute leadership.
Advance familiarity with online bioinformatic databases and systems, such as ggKbase, IMG, NCBI, CyVerse, and EMBL ENA.
Experience with the design, deployment, and maintenance of large-scale computing architecture and integration with databases and interfaces, i.e. DevOps. Specifically, advanced Unix-based system administration.
Expert knowledge of web, application, and data security concepts and methods.
Expert knowledge of clinical data security practices.
Advanced knowledge of microbial genomics, including knowledge of microbial genomic field sampling methods and genomic wet lab protocols.
Data science experience, specifically integrating biological and non-biological data; Understanding of database and search systems, such as SQL, MongoDB, and Elasticsearch.
Experience with effectively analyzing large data with modern visualization tools.
Experience synthesizing biological and informatics themes.
Demonstrated development of tools for analyzing large-scale sequence datasets.
High-level understanding of microbial phylogenetics.
Advanced statistical knowledge of analyzing microbial ecology data.
Ph.D. degree in a related area and or equivalent experience/training.
Thorough knowledge of genome assembly and reconstruction from complex metagenomic samples.
Ability to develop independent research themes and assist in the acquisition of funding from governmental agencies and private donors.
Knowledge and experience integrating microbial genomics in an ecological framework.
Ability to communicate through research articles and presentations. Demonstrated history publishing in a research journal.
Experience presenting orally at scientific conferences.
Ability to develop novel methods for the analysis of metagenomic and metatranscriptomic data.
Salary & Benefits
This is a full-time (40 hours per week), career position that is eligible for full UC benefits.
This position is exempt and paid monthly. The annual salary for this role is commensurate with experience within the range of $140,000.00 - $209,900.00.
This is a hybrid position, eligible for 50% remote capability.
Please submit your cover letter and resume when applying.
Equal Employment Opportunity
The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. For more information about your rights as an applicant see:
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