Postdoctoral fellowship in Neuropsychiatric Genomics: Biomarkers of Depression Treatment Response

Our interdisciplinary research group is looking for a self-motivated postdoctoral fellow with a strong computational background to join an initiative aimed at identifying neurobiological changes associated with response to fast-acting treatment interventions for depression. Our current projects incorporate genomic, clinical, neurocognitive, and neuroimaging measures in longitudinal studies, including total sleep deprivation, serial ketamine infusion, and electroconvulsive therapy for the treatment of severe, treatment-resistant depression. The applicant would be primarily responsible for the management and analysis of microarray gene expression data, but would also conduct integrative analyses in collaboration with other team members. The fellow will be expected to conduct several different kinds of analyses of the data (e.g., differential expression, WGCNA, predictive modeling), which will require staying up to date on developments in the field and analysis packages. The fellow will have opportunities to perform innovative studies, and will be expected to present/publish the results in scientific conferences/journals and participate in grant writing. The fellow will also have access to existing datasets that provide additional opportunities to explore relationships between neurocognitive function and genomic activity.

The postdoc should have completed a PhD at a major university in bioinformatics,  computational biology, neuroscience, biostatistics, computer science or related disciplines, with a strong research background, ability to work both independently as well as part of a team, and interest in applying these skills to the topic of depression. This position is collaborative and requires working with individuals from a range of backgrounds. A computational background and ability to handle large data sets is required, with experience in analysis and interpretation of omics data.

Additional qualifications:

 Experience in Unix/Linux shell

 Excellent skills in programming, and proficiency using R for statistical analysis

 Familiarity or experience with array-based genomic data

 Excellent oral and written communication skills

 Experience in psychiatry or neuroscience preferred

 Two-year commitment minimum

The position is based in the UCLA Department of Psychiatry and Biobehavioral Sciences. The fellow will be primarily supervised by Dr. Eliza Congdon; given the interdisciplinary nature of the position, opportunities for supervision are also available through collaborating PIs based on the applicants background and career plans. This position is supported by the UCLA Depression Grand Challenge – a campus-wide initiative aimed at cutting the burden of depression in half by 2050 primarily through the collection of a 100,000-person cohort.

Interested candidates should e-mail their CV, a brief statement of research interest, and the names and e-mails for three references to Eliza Congdon at econgdon@mednet.ucla.edu.