Dedicated exclusively to children and their families, The Hospital for Sick Children (SickKids) is one of the largest and most respected paediatric healthcare centres in the world. As innovators in child health, we lead and partner to improve the health of children through the integration of healthcare, leading-edge research and education. Our reputation would not have been built - nor could it be maintained - without the skills, knowledge and experience of the extraordinary people who come to work here every day.

SickKids is committed to ongoing learning and development, and features a caring and supportive work environment that combines exceptionally high standards of practice. When you join SickKids, you become part of our community. We share a commitment and determination to fulfill our vision of Healthier Children.

A Better World. Don't miss out on the prospect to work alongside the world's best in paediatric healthcare.

The Senior

Analyst will lead the analytical modeling work for the Cardiac-Neurodevelopment research program using quantitative brain MRI and machine learning to predict neurodevelopmental outcomes in infants with congenital heart disease. Reporting to the Heart Centre Research manager and Principal Investigator, the successful candidate will take a large neonatal brain MRI dataset, together with its associated clinical data, from curation through to validated predictive models.

Responsibilities span data stewardship, image processing and template construction, radiomics feature extraction, model development, and interpretability outputs. This is a hands-on technical-scientific role for someone equally comfortable building the processing pipeline, defending the analytic choices behind it, and explaining the results to a clinical audience. Here's What You'll Get To Do Take ownership of the study dataset end to end: data governance and stewardship, retrieval of pre- and post-operative neonatal brain MRI from the clinical imaging archive (PACS), and extraction and harmonization of demographic, perioperative, hospitalization course, sociodemographic, conventional MRI reporting, and neurodevelopmental outcome variables from the electronic medical record (EPIC)

Establish and document quality control procedures for the imaging data, combining automated and visual assessment, and maintain the source and integrity of the dataset throughout the project

Pre-process multi-contrast MRI data (e.g. T1- and T2-weighted, diffusion-weighted, susceptibility-weighted), including denoising, bias-field correction, intensity normalization, super-resolution reconstruction, co-registration, and deep learning based brain extraction

Construct a population-specific multi-contrast neonatal template and propagate anatomical labels to individual subjects, adapting existing atlases and pipelines to a congenital heart disease cohort and developing new methods where established tools do not transfer, including approaches suited to paired pre- and post-operative scans

Extract radiomics features across anatomically defined structures and whole-brain tiling, and assemble analysis-ready feature sets across imaging contrasts

Develop, train, and validate machine learning models predicting cognitive, language,



and motor outcomes, using regularized regression with nested cross-validation and hold-out testing, comparing clinical and conventional MRI reporting, radiomics, and combined feature sets, and extending to non-linear approaches where model diagnostics indicate

Assess patterns of missing clinical, imaging, and outcome data across the retrospective cohort, apply appropriate handling methods such as multiple imputation, and run sensitivity analyses to test the effect on model performance

Generate interpretability outputs, including predictor atlases that map model coefficients back to the brain, and feature importance summaries that make model behaviour conveniently interpretable to clinicians

Work with the institution's high-performance computing environment (and/or Digital Research Alliance of Canada, if needed and permitted by SickKids) to plan storage, parallelize processing, and manage computationally demanding analyses efficiently

Liaise with clinical, neuroimaging, and neurodevelopmental follow-up teams to resolve data questions and ensure the analytic work stays anchored to clinical reality

Lead and co-author manuscripts, present at scientific meetings, and contribute to lay summaries and other knowledge translation materials

Supervise trainees and students contributing to data curation, quality control, and analysis

Maintain reproducible, well-documented code and follow open science practices where permissible Here's What You'll Need Bachelor's degree in computer science, machine learning, biomedical engineering, neuroscience, or a closely related discipline, with medical imaging analysis experience.

Demonstrated expertise in machine learning applied to medical imaging, including regularized regression, cross-validation strategies, and the handling of high-dimensional, collinear feature sets; familiarity with non-linear methods is an asset

Experience working with large retrospective clinical datasets, including curating structured variables from electronic health records and principled approaches to missing data such as multiple imputation, and an understanding of how data completeness affects model performance and interpretation

Substantial experience processing and analyzing brain MRI data, ideally neonatal or paediatric, across multiple contrasts including structural, diffusion, and susceptibility-weighted imaging;

experience harmonizing imaging data across scanners or field strengths is an asset

Practical experience with template and atlas construction, registration, segmentation, and label propagation, including adapting or developing methods for populations where established adult and paediatric tools do not transfer cleanly

Experience with radiomics feature extraction and its application to outcome prediction

Strong programming skills in Python and shell scripting,



with working knowledge of established neuroimaging and analysis toolkits (for example ANTs, FSL, PyRadiomics, scikit-learn); familiarity with MATLAB and deep learning frameworks is an asset

Experience working in high-performance computing environments and managing large imaging datasets and their associated storage requirements

Sound judgement in handling sensitive health data, with a careful, documented approach to data organization, versioning, and reproducibility A record of peer-reviewed publication, including first-author work, and the ability to lead manuscript preparation

Excellent communication skills, with the ability to translate technical methods and model outputs for clinical and family audiences and to work productively within a multidisciplinary team

High attention to detail, strong problem-solving skills, and the ability to work independently, set priorities, and deliver against project milestones

Experience supervising trainees or students in a technical or analytic capacity is an asset

Demonstrated commitment and actions in advancing equity, diversity, and inclusion objectives Here's What You'll Love A focus on employee wellness with our new Staff Health and Well-being Strategy. Self-care helps us support others.

A hospital that welcomes and focuses on Equity, Diversity, and Inclusion.

The opportunity to make an impact. Regardless of your role or professional interest, you will be making a difference at SickKids and contributing to our vision of Healthier Children. A Better World.

For more on why you'll love working at SickKids, visit our careers site.

Employment Type

Temporary, 6-month contract

35 hours/week SickKids is committed to championing equity, diversity and inclusion in all that we do, fostering an intentionally inclusive and culturally safe environment that reflects the diversity of the patients, families and communities we serve. Learn more about workplace inclusion. If you require accommodation during the application process, please reach out to our aSKHR team.

SickKids can provide access and inclusion supports to eligible candidates to support their full engagement during the interview and selection process as well as to ensure candidates are able to perform their duties once successfully hired. If you are invited for an interview and require accommodation, please let us know at the time of your invitation to interview. Information received related to access, inclusion or accommodation will be addressed confidentially.

Technical difficulties? Email [email protected] with a short description of the issues you are experiencing. We will not accept resumes sent to this inbox but we are happy to respond to requests for technical assistance.

Tip: Combine your cover letter and resume into ONE document of 20 pages or less as you cannot upload multiple documents as part of your application. Every application is reviewed by a human recruiter and all hiring decisions are made by people. In some cases, AI-assisted tools are used to help review applications based on job-related qualifications. All positions posted on the SickKids Hospital's Careers Site represent current vacancies, unless otherwise posted in the .

📌 Senior Programmer/Analyst (Toronto)
🏢 The Hospital for Sick Children
📍 Toronto