TWO NIH-FUNDED POSTDOCS IN PARADISE ARE IMMEDIATELY AVAILABLE
1. Circuit + Molecular Neuroscience of Motivated Behavior, using rodent models of alcohol and substance use disorders, compulsive eating, obesity, and PTSD. Details here: https://academicjobsonline.org/ajo/jobs/26938
2. Machine Learning / Data Science / AI to identify new gene/phenotype risk variants and predict incidence and recurrence of human addiction and binge eating related disease using NIH All of Us and UK Biobank. Details here: https://academicjobsonline.org/ajo/jobs/26939
Position 1.The lab uses modern circuit and molecular neuroscience techniques, including activity- (TRAP2, eSARE), cell type- (Cre drivers), and projection-defined (AAV2retro, CAV2) causal approaches (optogenetics, chemogenetics) and molecular approaches (translatome, proteome, and spatial transcriptomics analyses). Classic neuroscience approaches also are used, including RNAScope, immunohistochemistry, qPCR, RNASeq, Western blotting, stereotaxic surgery, and both operant and naturalistic study of behavior. Potential areas of study include but are not limited to: □ reward-, stress- and anti-stress neurocircuitry in alcohol and substance use disorders □ molecular and circuitry bases of compulsive binge eating in models of food addiction □ co-morbidity of post-traumatic stress disorder with alcohol and substance use disorders □ translational neurobiology of addiction and relapse □ neuroimmunology of addictive disorders, including AUD □ sex differences in alcohol use disorder, addiction, binge eating, or obesity
Position 2. The Zorrilla lab studies the neural substrates of motivated behavior and psychiatric genetics using large human multi-omic, multi-phenotype, big data human datasets that include electronic health registries, neuroimaging, biomarker, and lifestyle data (e.g., All Of Us, UK Biobank) as well as RNASeq datasets obtained from orthologous animal models of binge eating behavior, alcohol use disorder, drug addiction, obesity, and post-traumatic emotional disorders. The successful applicant for this position will have advanced computational and data science experience that includes applying machine learning, deep learning, and/or generative model approaches to large, multi-dimensional datasets (e.g., >150k cases with whole genome sequences) for identifying predictive gene variants and phenotypes, prediction of diagnostic incidence or recurrence, modeling latent or manifest continuous traits, and developing risk score algorithms.
The Zorrilla Lab is in a rich intellectual environment, affiliated with the Scripps Departments of Molecular Medicine and Neuroscience, the National Institute on Alcohol Abuse and Alcoholism (NIAAA)-funded Scripps T32 Institutional Postdoctoral Training Program, the NIAAA-funded Scripps P60 Alcohol Research Center of Excellence, the Pearson Center for Alcohol and Addiction Research, and the University of California-San Diego (UCSD) Neuroscience Graduate Group.
Successful trainees will gain cutting-edge technical training and develop skills needed to compete for independent funding and transition to independence. This postdoctoral position offers salary levels above NIH minimums as well as employee benefits from The Scripps Research Institute.
Pending Ph.D. applicants are acceptable.
Eligible candidates have the possibility of being appointed to our NIAAA-funded T32 training grant and becoming affiliate members of the P60 Center funded by NIAAA and the Pearson Center. Appointment to the T32 training grant requires candidates to be a U.S. Citizen or permanent resident.
The Scripps Research Institute is an Equal Opportunity Employer. All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other legally protected characteristic or status.