Programmer Analyst I: Genomics – Bioinformatics – Computational Biology

Job Location
La Jolla, CA 92093
Job Description

The Programmer Analyst will perform programming and/ or assist in design and analysis of systems to decipher the role of Single Nucleotide Polymorphisms and Copy number variation (CNVs) in psychiatric disorders. Maintain a computational pipeline (consist of custom software) for processing and analyzing large volumes of whole genome sequence data. Responsible for reporting the performance along with the specificity and sensitivity of each of these platforms so that they can be customized towards the overall goal of the project. Will help develop algorithms for filtering and refining the dataset. Some qualifications include:


·         1. Knowledge in the development of bioinformatics tools as well as biological sciences in the field of genomics or  

·             computational biology.

·         2. Understanding of whole genome sequencing, genome assembly, and short-reads sequencing technology and

·             application.

·         3. Knowledge in algorithm development for genome assembly.

·         4. Demonstrated programming skills in Java, Python, R with the ability to work comfortably in a Linux environment.

·         5. Demonstrated knowledge/experience in a specified computing environment and operating systems, including Unix

·             and Linux.

How to Apply

Applicants should apply at (Reference #73303)

Jonathan Sebat, Ph. D.

[email protected]

Chief, Beyster Center for Molecular Genomics of Neuropsychiatric Diseases
 Institute for Genomic Medicine

Associate Professor
Department of Psychiatry
Department of Cellular and Molecular Medicine
University Of California, San Diego
La Jolla, CA 92093-0667

About Our Organization

A Scientific Research Programmer Analyst I in genome informatics and computational biology is available in the Beyster Center for Genomics of Psychiatric Disease and the Institute for Genomic Medicine at UC San Diego ( Our laboratory is developing novel approaches for the identification of risk genes for neuropsychiatric disorders, and we are initiating a new study focused on understanding the contribution of germline mutation to disease risk in Autism. We seek to understand the genetic basis of disease by Whole Genome Sequencing (WGS) in families, and by integrating data on de novo mutation and inherited genetic variation, including copy number variants (CNVs), nucleotide substitutions and indels ( We are currently leading multiple large scale genetic studies of autism and schizophrenia.

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