Bioinformatics Programmer IV

University of California San Francisco
94102, San Francisco
Jul 17, 2018
Required Education
Masters Degree/MBA
Position Type
Full time

In this role, the individual will be part of a team responsible for design, construction, and maintenance of a genomic analysis pipeline for clinical cancer samples that communicates with sequencing core services, laboratory information management systems and clinical reporting software.

Under the general direction of the Associate Director of Informatics for CCGL, the Bioinformatics Programmer will design and develop new components for our internally developed cloud-based sequence analysis pipeline to support new and enhanced clinical testing. Features slated for development include gene fusion detection via RNAseq, detection of viral sequences, and detection of mutational signatures. Other new software developed will provide support for automating aspects of sample analysis and error reporting and integration with other clinical systems. Additional responsibilities will include supporting the development of target capture panels and test validation as well as quarterly data analysis to improve QC and support clinical annotation.

The Department of Pathology at UCSF aims to achieve the highest standards in patient care, research and education. The Department provides diagnostic pathology services in a wide variety of subspecialties with highly trained subspecialists who are recognized nationally and internationally for their expertise. The Department’s research programs are diverse and interface with a wealth of basic and translational research programs that are a hallmark of UCSF.

The mission of the Clinical Cancer Genomics Laboratory (CCGL) at UCSF is to develop and validate genomic testing to support cancer clinical care and research. The CCGL provides the UCSF500 Cancer Gene Panel assay, a molecular test profiling DNA from tumor and normal tissue to identify mutations that may drive a patient’s cancer and aid in diagnosis and treatment.

The University of California, San Francisco (UCSF) is a leading university dedicated to promoting health worldwide through advanced biomedical research, graduate-level education in the life sciences and health professions, and excellence in patient care. It is the only campus in the 10-campus UC system dedicated exclusively to the health sciences.

Required Qualifications
Master’s degree in Bioinformatics or related field and four years relevant experience
Minimum five years of experience with Illumina sequencing data, genetic variant calling, variant analysis, annotation and filtering
In-depth knowledge of bioinformatics methods and data structures
 In-depth knowledge of bioinformatics programming design, modification and implementation
 Python, R, Unix/Linux OS and shell scripting, and associated libraries
Strong knowledge of statistics and experience working with large genomics datasets
In-depth knowledge of genomics and modern cancer biology. and applicable field of research
Advanced interpersonal skills in order to work with both technical and non-technical personnel at all levels in the organization, including senior project leadership
 Ability to communicate technical information in a clear and concise manner

Preferred Qualifications
 PhD in Bioinformatics
Advanced understanding of relational databases, web interfaces and operating systems
 Advanced project management skills
 Advanced ability to interface with management on a regular basis
Ability to lead a team, meet deadlines and demonstrate advanced problem solving skills
In-depth knowledge of web, application and data security concepts and methods
Familiarity with cancer variant databases and clinical ontologies



The University of California San Francisco 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, age, protected veteran or disabled status, or genetic information.<img height=1 width=1 border=0 src= />

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