Candidates are being considered for a full-time Neuroimaging Data Analyst position for the Maryland Neuroimaging Center (www.mnc.umd.edu) at the University of Maryland, College Park. This is a shared position between the MNC and Dr. Luiz Pessoa’s Laboratory of Cognition and Emotion (http://lce.umd.edu/). The data analyst will be involved in the analysis of neuroimaging data (especially functional MRI) using standard group analysis, in addition to advanced methods including graph theory/network analysis, machine learning, and neural networks, and designing novel experimental fMRI and behavioral paradigms. The data analyst will be involved in multiple projects and expected to be a co-author in multiple research papers.
Salary will be competitive commensurate with experience and includes health benefits. Application review will begin immediately. This is a 1-year position with the possibility of renewal for subsequent years, contingent on performance and funding. The University of Maryland is an equal opportunity affirmative action employer with a commitment to racial, cultural, and gender diversity. Women and minorities are encouraged to apply.
To apply please email your application to Anastasiia Khibovska (firstname.lastname@example.org). Application materials should include a cover letter detailing qualifications and interest, CV, relevant coursework or transcript, and at least 2 references who can provide letters upon request.
The ideal applicant will have a Master’s degree in Engineering/Computer Science (or related field) and experience with MRI data acquisition and analysis (AFNI, SPM, FSL, Freesurfer, etc.). Computer programming experience is necessary (Python, Matlab, R, etc.), including familiarity with Linux environments.
Internal Number: Neuroimaging Data Analyst
About Lab of Cognition and Emotion at the University of Maryland
We employ behavioral and functional MRI methods to study interactions between cognition and emotion/motivation. Our view is that brain systems are highly interactive and that modular approaches to understanding the mind-brain are fundamentally problematic.
An additional focus of our research centers on the development of statistical and computational tools for the analysis of functional MRI data to allow a rigorous mapping between brain and behavior.