BIOINFORMATICS PROGR

About the role

The Cardiovascular Genetics Center at University of California, San Francisco is seeking an experienced bioinfomatician to facilitate 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.

Responsibilities

• 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.
• Develop and utilize computational tools and systems to analyze and interpret biological or other research data.
• Utilize and develop 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.
• Analyze 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.
• Analyze genome sequencing data including whole exome- and whole genome sequencing to discern rare and common variants implicated in cardiovascular disease.
• Implement machine learning algorithms to analyze biological datasets.

Requirements

• 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
• Familiarity with 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
• In-depth knowledge of genomic databases, tools, and statistical frameworks

Qualifications

• 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
• Familiarity with 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
• In-depth knowledge of genomic databases, tools, and statistical frameworks