**Data Scientist / Bioinformatician / Statistician**
– **Location:** UCSF Mission Bay
– **Department:** Psychiatry
– **Hours:** Monday – Friday, 9:00 am – 5:00 pm
– **Full Benefits**
**JOB OVERVIEW**
This position is still available as of November 10, 2016.
The Willsey Lab specializes in bioinformatic analysis of high throughput genetic data and in systems biological analyses of multidimensional biological datasets. We generate and analyze whole exome and whole genome sequencing data to identify genes associated with human disorders, such as autism spectrum disorder and Tourette syndrome. We then leverage systems approaches, integrating relevant datasets (e.g, RNA-Seq gene expression data from the developing brain), to understand the connection between the identified genes and pathology of the disorder. Hypotheses are tested in model systems, such as neurons derived from human induced pleuripotent stem cells, organized into a 3D model of the developing human cortex (human cortical spheroids).
The Data Scientist / Bioinformatician / Statistician will work with PhD and postdoctoral-level bioinformaticians to further this research and support the computing needs of the laboratory. In particular, the successful applicant will design pipelines and algorithms for data processing, and execute these pipelines on large datasets. He/she will also analyze and visualize data, manage the high performance computational environment, and help with code development. There will be many opportunities for creativity and problem solving, as well as independent projects.
While experience in biology, genetics, and/or statistics would be a great asset, we are especially keen to hire an individual who is highly motivated and capable of working both independently and as part of a team.
>$100k salary possible depending on experience and qualifications.
**DEPARTMENT OF PSYCHIATRY**
The UCSF Department of Psychiatry is among the nation’s foremost resources in the field of child, adolescent and adult mental health. Psychiatry faculty members are recognized for their leadership roles in state-of-the-art, comprehensive and compassionate patient care, pioneering research, excellence in training the next generation of leaders, advancing public policy to advance mental health, and commitment to diversity.
**ABOUT UCSF**
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.
– Expertise in R
– Experience in R package design
– Experience in R Shiny web apps
– Proficient at data visualization
– MS in Computer Science/Biological Sciences, Statistics, or equivalent strongly preferred
– Prior systems administration with UNIX/Linux
– Proven record of excelling in a large team environment (15 plus individuals) but still possess an independent work ethic
– Proficient at Python and/or Perl programming
– Experience C/C++, Java, html, PHP, SQL programming
– Familiarity with statistical analysis
– Proven ability to work within a team to accomplish specific goals at specified times
– Outstanding job references
– Demonstrates excellent attendance and professionalism
– Excellent written and oral communication skills
– Strong organizational skills
– Interested in learning about genetics
– Attention to detail
– Ability to pick up new techniques quickly
– Excellent problem solving skills
– PhD in Computer Science/Statistics/Biological Sciences, or equivalent is a plus
– Background in biological data processing, especially in human genetics
– Experience with high performance clusters
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.