Scientific Associate - Pre-clinical Research

CAMHToronto, ON
CA$93,823 - CA$117,278Onsite

About The Position

CAMH’s Campbell Family Mental Health Research Institute (CFMHRI) is seeking a full-time, permanent Scientific Associate specializing in neural data systems and behavioral analytics. The Scientific Associate will serve as a central technical and scientific lead within the laboratory, with primary responsibility for developing, standardizing, and maintaining pipelines for neural and behavioral data acquisition, analysis, documentation, and open data sharing. This role integrates data engineering, experimental design, and personnel training to ensure rigor, reproducibility, and scalability of research operations. The Scientific Associate will also lead efforts to implement and validate emerging technologies for behavioral tracking and pose estimation, and to integrate these measures with neural recordings. Reporting to the Principal Investigator, this position will play a key role in shaping lab-wide infrastructure and mentoring trainees in best practices across experimental and computational workflows.

Requirements

  • Specialization in neural data systems and behavioral analytics.
  • Experience in developing, standardizing, and maintaining pipelines for data acquisition, analysis, documentation, and open data sharing.
  • Proficiency in data engineering.
  • Experience in experimental design.
  • Experience in personnel training.
  • Experience in implementing and validating emerging technologies for behavioral tracking and pose estimation.
  • Experience integrating behavioral measures with neural recordings.
  • Experience in shaping lab-wide infrastructure.
  • Experience mentoring trainees in experimental and computational workflows.

Responsibilities

  • Developing, standardizing, and maintaining pipelines for neural and behavioral data acquisition, analysis, documentation, and open data sharing.
  • Integrating data engineering, experimental design, and personnel training to ensure rigor, reproducibility, and scalability of research operations.
  • Leading efforts to implement and validate emerging technologies for behavioral tracking and pose estimation.
  • Integrating behavioral tracking and pose estimation measures with neural recordings.
  • Shaping lab-wide infrastructure.
  • Mentoring trainees in best practices across experimental and computational workflows.
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