This Gates foundation grant-funded position will focus on the analysis of existing developmental neuroimaging datasets (fNIRS/fMRI) to predict developmental outcomes. The focus of this project is on dynamic changes during experience (i.e., learning), the emergence of large-scale neural networks (i.e., functional connectivity) and distributed representational patterns across the cortex (i.e., decoding or use of machine learning methods) in these fNIRS datasets.
Researchers with interests in early neural and cognitive development with prior experience with developmental neuroimaging (fNIRS, EEG, fMRI, other) are encouraged to apply. Ideally, candidates will have knowledge of relevant statistical software & programming tools (e.g. MATLAB, R).
Candidates must have a Ph.D. and show evidence of publication-quality dissertation research. Candidates must have research experience with developmental populations and/or neuroimaging (with adults OR developmental populations, any modality).
Please submit a CV, a cover letter describing academic and research goals, as well as relevant research experience directly to Dr. Emberson. In addition, include 2 papers or posters of your research. Applicants are required to include contact information for at least 2 references but letters are not required at this time. References will be contacted for a short-list of candidates only. Contact Dr. Lauren Emberson () for additional questions.