We have a vacancy for 2 excellent post-doctoral scholars to work on a project focusing on examining the hierarchical structure of the NIH Research Domain Criteria (RDoC) framework using large-scale data-driven computational approaches. The RDoC framework, currently only for research, ultimately aims at facilitating the development of psychiatric nosology (disorder-classification system) based upon primary behavioral functions and their associated biological features that the brain has evolved to carry out. In this project, using large-scale fMRI datasets (e.g., ABCD study), we specifically aim to examine whether (and to what degree): (1) RDoC constructs overlap across domains (2) within-domain constructs relate to similar dimensions of psychopathology; and (3) task-free paradigms (e.g., resting-state) can be mined to extract similar domain-specific information that is usually extracted using specific task-based paradigms. By addressing these three key questions, our central goal is to provide the much-needed bottom-up examination of the RDoC framework to pave a pathway for its refinement and translation.
The project is hosted by the Brain Dynamics Lab, situated within the Division of Interdisciplinary Brain Sciences in the Department of Psychiatry & Behavioral Science at Stanford University School of Medicine, under the supervision of Dr. Manish Saggar (firstname.lastname@example.org) and integrated into the wider academic research environment at the Stanford University.
The candidate will have the opportunity to collaborate with top neuroscientists, psychologists, computational scientists, clinicians, and statisticians at Stanford. Additionally, access to cutting-edge neuroimaging and computational technologies will allow for the development of the candidate’s own research. Multidisciplinary aspects of this project allow for diverse exploration of neuroimaging-based biomarkers for psychiatric disorders.
Qualifications: We are looking for highly self-motivated candidates who are curious and enthusiastic about scientific research and who will work with others in our lab and in the institute to solve problems and contribute to high-quality neuroscience investigations. As our ideal candidate you have a doctoral degree in a numerate discipline such as psychology, statistics, computer science, engineering, computational / cognitive neuroscience or other relevant field of study. You also have a proactive attitude, good written and oral communication skills, and you can work effectively in an interdisciplinary team. Experience in neuroimaging analysis is a must.
Additional experience in any of these is a plus:
- expertise in statistical methods for neuroimaging analysis (e.g., functional connectivity analysis, ICA, structure equation modeling)
- expertise in network neuroscience (e.g., Topological Data Analysis, Edge-time series)
- expertise in fMRI data analysis (e.g., using FSL, AFNI, SPM, fMRIPrep, XCPEngine) and coding (e.g., Matlab, Python, R, BASH)
- expertise in academic writing
- experience with large scale consortium data