DESCRIPTION

The University of California at San Diego (UCSD) Department of Psychiatry is one of the most innovative and productive academic departments in the country, offering challenging career opportunities in the diverse areas of advanced educational programs, cutting-edge research, and state-of-the-art clinical services. The department is committed to offering a dynamic learning environment and growing opportunities to its talented and dedicated employees.

The Statistical Genetics Data Analyst III will support our NIH-funded projects focused on the analysis of whole-genome, exome and genome-wide association (GWAS) data in psychiatric and neurodevelopmental disorders. The goal of our research is understand how the combined effects of rare genetic variation and common polygenic risk influence brain development and dimensional measures of cognitive function, and ultimately, how genes shape the clinical features of mental disorders.

Under the direction of Dr Jonathan Sebat, the Analyst will carry out statistical genetic analyses of large well-powered datasets from our laboratory and from international collaborations such as the Simons Powering Autism Research (SPARK), Psychiatric Genomics Consortium (PGC), the Genes 2 Mental Health Network (G2MH), the UK Biobank and the PsychEncode project. The Analyst will perform moderately to highly complex analysis of whole genome sequence datasets including variant calling and genotyping, analysis of gene-trait relationships, functional characterization of genes, and will support multi-omics analysis of functional genomic data (RNA Sequencing, Ribosome profiling, Hi-C).Experience with analysis of DNA Sequencing data is required. A major focus of this research will be whole genome and exome sequences collected short read (Illumina) or long read (Pacific Biosciences, Oxford Nanopore) and sequencing platforms. Analysis methods may include, but not be limited to, genotyping of structural variants (SVs) and tandem repeats (TRs), genetic association studies, analysis of heritability (LD score regression), linear regression, factor analysis, nonparametric methods, logistic regression, survival analysis, discriminant analysis, permutation methods, tree-structured methods, cross-validated misclassification probability estimation, principle components, multiple comparison methods, and power analysis and existing statistical genetic software such as PLINK. These analyses will be conducted in a combination of scripting and statistical languages including Python and R. These efforts involve extensive usage of UNIX based super-computing systems, including programming statistical routines to be optimally run in such environments.

Analyst will coordinate with and provide training to entry-level bioinformatics staff and graduate and postdoctoral trainees. Responsibilities include data analyses and generation of figures for new grant applications and independently write analytical method sections relating to the statistical analysis sections. Uses advanced knowledge and methodological skills to make independent contributions to the ongoing research, from conceptualization and planning to the writing of manuscripts. The Analyst is expected to be active in scholarly activities at UCSD, including regular attendance of relevant seminars in genomics, bioinformatics and computer science. There are ample opportunities for publication of scholarly work and travel to international scientific meetings, but frequent travel is not required.

MINIMUM QUALIFICATIONS

• Seven years of related experience, education/training, OR a Bachelor's degree in related area plus three years of related experience/training.

• Thorough knowledge of research function. Comprehensive knowledge to contribute independent ideas to research and develop research plan.

• Thorough skills associated with statistical analysis and systems programming. Advanced working experience with statistical methods and models incorporating a broad range of variable types and traditional and modern statistical approaches.

• Thorough skills in analysis and consultation. Demonstrate expertise working with statistical methods and models incorporating a wide range of variable types for analysis of variance and covariance, multiple linear, logistic models, survival analysis and longitudinal models.

• Skills to communicate complex information in a clear and concise manner both verbally and in writing. Excellent verbal and written communication skills, with