The Goubran, Hynynen, and Davidson labs at the Sunnybrook Research Institute, University of Toronto, are seeking a motivated Research Assistant to work on a range of projects at the intersection of neuromodulation, neuroimaging, and focused ultrasound (FUS). Our interdisciplinary teams lead several clinical and preclinical studies at Sunnybrook centred on developing and characterizing treatment strategies for brain disorders, including FUS neuromodulation exposures for depression and obsessive compulsive disorder. You will be involved with a broad range of tasks, including the development and optimization of a neuroimaging pipeline to analyze fMRI data from rabbits. This pipeline will be critical in assessing the impacts of FUS neuromodulation exposures on brain function prior to clinical translation. Other tasks will include processing/statistical analysis of medical images (particularly fMRI preprocessing and analysis), optimizing computational pipelines, building an imaging database, maintaining repositories, and contributing to publications. We collaborate with a diverse and multidisciplinary team of researchers, including computer scientists, physicists, neurologists, radiologists, and neuroscientists, within a dynamic and collegial environment.

Summary of Duties:

• Developing and optimizing a neuroimaging pipeline for rabbits and computational tools to analyze preclinical fMRI data.

• Similarly, developing and optimizing neuroimaging pipelines in human clinical trials.

• Contributing to research projects, international collaborations, grant writing, and publishing papers.

• Writing and submitting REB applications and other administrative tasks.

Presenting at conferences and workshops.

Qualifications:

• Post-secondary degree in computer science, biomedical engineering, bioinformatics, computational neuroscience, or a related discipline (M.Sc. preferred).

• Computer programming experience, with demonstrated skills in Python.

• Intermediate knowledge of neuroimaging software and toolkits (e.g., Freesurfer, FSL, ITK, fMRIPrep, CONN)

• Intermediate knowledge of Linux, including shell scripting.

• Proven ability to work independently as well as collaboratively.

• Excellent verbal and written communication skills in English.

Assets:

• Experience with resting-state or task fMRI data and analyses
• Python software packaging, virtual environments, High-Performance Computing (Slurm), Docker, Jupyter/IPython.
• Experience with systems architecture/imaging databases for computational pipeline design.
• Experience with version control systems, such as Git.
• Prior research experience (course-based allowed).
• Experience with biostatistics/statistical analysis and Python/R or equivalent software.
• Experience with Machine Learning model development and evaluation.

To apply for this position, please follow the link:

Send a (1) cover letter (max. 1/2 page), (2) Curriculum Vitae, (3) (un-)official transcript, and (4) the contact info of three potential references.