UCSF

Public health sciences university in San Francisco

Bioinformatics Programmer 3

Life Sciences ResearchConfirmed live in the last 24 hours

Full-timeSan Francisco, CA, USANo salary listedIn-person

About the Job

Requirements

A bachelor's degree in biological science, computational/programming, or a related area, or equivalent experience or training.
At least 3 years of relevant work experience in bioinformatics or computational biology.
Thorough knowledge of bioinformatics programming design, modification, and implementation using Python, R, or equivalent languages.
Understanding of relational databases, web interfaces, and operating systems.
Strong project management skills.
Thorough knowledge of modern biology and the applicable research field.
Communication skills to work with technical and non-technical personnel across multiple fields of expertise and organizational levels.
Ability to communicate technical information clearly and concisely.
Ability to interface with management regularly.
Ability to work independently or as part of a team, learn quickly, meet deadlines, and demonstrate problem-solving skills.
Thorough knowledge of web, application, and data security concepts and methods.
Familiarity with cloud-based computing and high-performance computing environments.
Proven expertise, reflected in publication record, analyzing high-throughput sequencing datasets, including RNA sequencing, ATAC sequencing, and chromatin occupancy studies.
Thorough, in-depth knowledge of genomic databases, tools, and statistical frameworks.

Responsibilities

Design and implement analysis pipelines for computational biology research, including experimentally generated datasets and patient-derived genomic data from UCSF patients and public data repositories.
Develop and use computational tools and systems to analyze and interpret biological or other research data.
Use and develop algorithms, computational techniques, and statistical methodologies.
Help design new experiments.
Implement end-user needs in database searching and integration.
Maintain computational infrastructure and track sample and information flow for large-scale studies.
Provide web-based bioinformatics and access to public and proprietary databases.
Analyze experimentally generated biological datasets, including bulk and single-cell multiomics sequencing, epigenomics data such as ChIP-seq and CUT&RUN, and imaging data such as spatial transcriptomics.
Integrate experimental data with publicly available genomic and expression datasets, including UK Biobank, All of Us, and Heart Cell Atlas.
Analyze whole-exome and whole-genome sequencing data to identify rare and common variants implicated in cardiovascular disease.
Implement machine-learning algorithms to analyze biological datasets.
Collaborate frequently with bench scientists and clinicians.

Desired Qualifications

A PhD in Bioinformatics or a closely related field.

The Cardiovascular Genetics Center at University of California, San Francisco is seeking an experienced bioinfomatician to faciliate several lines of research that relate broadly to inherited forms of cardiovascular disease, regulation of gene expression in health and disease, and personalized genetic medicine. The incumbent will work closely with prinicpal investigators within the Genetic Center to design and implement analysis pipelines in several broad areas of computational biology including analysis of experimentally generated datasets in basic research, and analysis of patient-derived genomic data from UCSF patients as well as publicly available data repositories. The goal will be to make fundamental biological discoveries that can ultimately be translated to understanding, prevent, and treat heritable cardiovascular diseases.

More specifically, the role involves developing and utilizing computational tools and systems to analyze and interpret biological or other research data. Utilizes and develops algorithms, computational techniques, and statistical methodologies. Helps in the design of new experiments. Implements end-user needs in database searching and integration. Maintains the computational infrastructure and tracks the flow of samples and information for large-scale studies. Provides web-based bioinformatics and access to public and proprietary databases.

The scope of work will include anayzing biological datasets generated experimentally including but not limited to bulk and single cell multiomics sequencing, epigenomics data including ChIP-Seq and CUT&RUN, and imaging data including spatial transcriptomics; overlapping experimental data with publicaly available genomic and expression datasets including UK Biobank, All of Us, Heart Cell Atlas, and similar datasets. There will also be analysis of genome sequencing data including whole exome- and whole genome sequencing to discern rare and common variants implicated in cardiovascular disease.The incumbent will also implement machine learning algorithms to analyze biological datasets. There will be frequent collaboration with bench scientists and clinicians in a highly collegial and stimulating scientific environment.

Required Qualifications

Bachelor's degree in biological science, computational / programming, or related area and / or equivalent experience / training
A minimum of 3 years of relevant work experience in bioinformatics or computational biology
Thorough knowledge of bioinformatics programming design, modification and implementation in relevant languages such as Python, R, and/or equivalent
Understanding of relational databases, web interfaces, and operating systems
Strong project management skills
Thorough knowledge of modern biology and applicable field of research
Communication skills to work with both technical and non-technical personnel in multiple fields of expertise and at various levels in the organization
Ability to communicate technical information in a clear and concise manner
Ability to interface with management on a regular basis
Self motivated, work independently or as part of a team, able to learn quickly, meet deadlines and demonstrate problem solving skills
Thorough knowledge of web, application and data security concepts and methods
Familiarity with cloud-based computing and high-performance computing environments
Proven expertise, as reflected in publication record, in analyzing high-throughput sequencing datasets, including RNA-sequencing, ATAC-sequencing, and chromatin occupancy studies
Thorough In-depth knowledge of genomic databases, tools, and statistical frameworks

Preferred Qualifications

PhD in Bioinformatics or a closely related field

About the Company

UCSF

Public health sciences university in San Francisco

UC San Francisco is a public research university in San Francisco focused solely on health sciences, combining professional education with biomedical research and patient care. Its schools of dentistry, medicine, nursing and pharmacy train clinicians and scientists, while teams investigate cancer, immunology, genomics and neuroscience. UCSF Medical Center and Benioff Children's Hospitals connect clinical care with faculty research and training, and university clinics serve patients across Northern California. Founded in 1864, UCSF is the University of California campus dedicated to graduate and professional education and biomedical research, based in San Francisco.

Company size: 10,001+
Company stage: Not listed
Total funding: Not listed
Headquarters: Not listed
Founded: 1864

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