Data Analyst / Research Technician

Applications are currently being invited for a data analyst position in the Computational Neuroimaging Laboratories within the Center for the Biomedical Imaging and Neuromodulation (C-BIN), under the direction of Alexandre R. Franco, PhD. A primary responsibility of this position will be the processing of large scale neuroimaging datasets for C-BIN investigators and collaborators, using state-of-the-art image processing pipelines (e.g., functional MRI, structural MRI, diffusion imaging and arterial spin labeling). The analyst will also support investigators in the analysis of datasets using a combination of univariate and multivariate analytic approaches (e.g., machine learning theory). Successful candidates must have sufficient technical skills (e.g., C/C++, Python, R, bash scripts) to independently modify processing pipelines and apply novel data analysis strategies. The analysis will also be expected to maintain the neuroinformatics infrastructure of CBIN. As experience grows, the analyst will be expected to provide supervision for junior researchers in their analytic efforts.

• Implement novel signal processing, machine learning, and statistical methods in Python, R and C/C++.
• Perform image processing and analysis on very large fMRI, MRI, DTI and ASL datasets using high performance computing infrastructures.
• Liaise with C-BIN members and collaborators.
• Maintain neuroinformatics infrastructure
• Mentor and in some cases supervise junior lab members such as other research associates and graduate students.

The minimum qualifications for a successful candidate include:
• BS in Electrical Engineering, Biomedical Engineering, Computer Engineering, Computer Science, or other related scientific fields. MS preferred.
• Proficient in programming C/C++, Matlab, Python or R and proficiency in Linux environment.
• Extensive experience with one or more MRI data analysis packages (e.g., AFNI, FSL, SPM, or Freesurfer)
• Prior experience with functional MRI or diffusion imaging processing pipelines
• Proficiency in the application of multivariate analytic techniques. Machine learning theory strongly preferred.
• Knowledge of cognitive and/or clinical neuroscience (preferred).
• Ability to work effectively in a very collaborative and multidisciplinary environment.

Anticipated start date: as soon as possible

For more information about the position and how to apply, please use the following link: