Postdoctoral position in computational modeling and data science at the Stress Neuroimaging Lab (SNL) at UCSD
The Stress Neuroimaging Lab (SNL; PIs: Alan Simmons, PhD and Katia Harlé, PhD) is recruiting a postdoctoral fellow to join the lab. Research in the lab uses behavioral tasks (affective processing and decision-making), functional and structural neuroimaging, cognitive computational modeling, and machine learning approaches to investigate learning alterations and treatment responsiveness in Post-Traumatic Stress Disorder (PTSD), depression, and related disorders.
This position is ideal for someone with experience in some or all of the following: advanced predictive statistical methods, computational modeling of behavior, functional magnetic resonance imaging (fMRI), clustering, big data analysis; and who wishes to gain or deepen expertise in these areas. The postdoctoral fellow will be expected to analyze and model behavioral and neuroimaging data, present and publish findings, apply for external funding, and assist with research staff training and lab management. Anticipated start date is Fall 2024.
Required skills/qualifications:
- A PhD (by start of employment) in Psychology, Neuroscience, Cognitive Science, or related field
- Expertise in advanced quantitative/statistical methods (e.g., machine learning, computational modeling, multilevel and/or structural equation modeling, univariate and/or multivariate fMRI/EEG analysis)
- Knowledge of R, MatLab, Afni, shell scripts, or similar programming languages
- Knowledge Python and ANTS a strength
- Interest in mechanisms of psychopathology, particularly trauma, anxiety, and depression
To apply, please submit the following at here and via email to Katia Harlé (kharle@health.ucsd.edu) or Alan Simmons (ansimmons@health.ucsd.edu)
- Cover letter detailing fit for lab based on research interests and required skills/qualifications
- CV
- Names and contact information for three professional references
- Representative publication (can be a preprint or in prep)