The Wall Lab in the Department of Pediatrics, Division of Systems Medicine, and Department of Biomedical Data Science at Stanford University seeks a talented, highly motivated researcher with a background in computational genomics. The group primarily focuses on identifying genetic risk factors in Autism Spectrum Disorder (ASD) with whole genome sequencing (WGS) datasets and analysis of associated phenotypes. Our lab has collected a uniquely diverse and comprehensive set of human genomic and phenotypic datasets, including the AGRE/iHART WGS collection of over 1000 families with multiple children with ASD (the largest of its kind). These unparalleled data and compute resources provide a unique opportunity to analyze large-scale whole genome data sets in the cloud, to disentangle the complex genotype-to-phenotype map of polygenic ASD, and to work closely with a diverse group of exciting transdisciplinary collaborators.
Open to U.S. applicants only.
Responsibilities for this position include:
● To lead development and implementation of novel computational methods and tools for analysis of WGS data, focusing on non-coding regions.
● To provide bioinformatics resources to the members of the lab.
● To monitor and evaluate emerging bioinformatics technologies.
● To implement data resource architectures capable of managing and providing efficient access to petabyte-scale genomic data.
The candidate will be called upon to present work at national and international research conferences.
● Ph.D. in computational biology/genomics or related discipline.
● Proven understanding and experience in WGS pipelines, analyses, and databases.
● Experience with WGS analysis tools: BWA, GATK, etc.
● Experience with using Linux/Unix/HPC command line.
● Experience with statistical analysis and diagnostics.
● Programming skills with proficiency in Python, Java, and/or R.
● Experience with cloud development ecosystems – Google or AWS.
● Ability to present and visualize outputs to multidisciplinary audience.
● Ability to work independently and in small teams.
● Experience with computational algorithm design and analysis.
● Experience with collaborative software design in a small team setting.
Required Application Materials:
● CV, Statement of interest, and list of 3 references