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Reference Number: 000001688
Posted Date: 6/15/2022
Closing Date: 7/15/2022

Department: LTRI - Radiomics & Machine Learning Lab
Position: Scientific Associate

POSITION TITLE  Scientific Associate
DEPARTMENT  LTRI - Radiomics & Machine Learning Lab
EMPLOYMENT TYPE  Temporary Full-Time (12 months)
HOURS OF WORK  37.5 hours per week
REPORTS TO  Senior Clinician Scientist

The Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, a University of Toronto affiliated research center, is one of the world's leading centers in biomedical research.  With ground-breaking discoveries in research areas such as diabetes, genetic disorders, cancer and women’s and infants’ health, the Institute is committed to excellence in health research and the training of young investigators.  Strong partnerships with the clinical programs of Mount Sinai Hospital ensure that scientific knowledge is used to promote human health.  Your significant contributions will assist in maintaining our momentum in advancing our research.


Department description

At the Radiomics & Machine Learning Lab at Lunenfeld-Tanenbaum Research Institute, Sinai Health System, we conduct research in design and development of artificial intelligence solutions for medical imaging. The data sources are imaging modalities such as MRI and CT and the use cases are focused on clinical translation. We are part of the AI Center in the Joint Dept. of Medical Imaging which encompasses the imaging Departments of the Toronto General Hospital, Sinai Health System, Princess Margaret Hospital, Toronto Western Hospital and Womens College Hospital.


Position Overview:

The Scientific Associate will work in a support role in maintaining the hardware and software machine learning platforms in the lab. The successful candidate will work with the lab members to help produce high quality research, algorithms, manuscripts, and documents as part of team research. The successful candidate will report to the Principal Investigator (PI) and Director of the Lab, Dr. Haider. Opportunities for publication co-authorship will be available depending on level of academic contribution.



  • Ensure smooth operations of computer hardware and software platforms tailored for machine learning
  • Ensure maintenance of data repositories and image analysis pipelines
  • Algorithm implementation/coding for medical image analysis, machine learning, and statistical modeling solutions:
  • Perform necessary quality control procedures to ensure accuracy and completeness of the research data
  • Train, test and validate classifiers for medical imaging use cases using a Nvidia GPU cluster.
  • Asist in papers/abstracts/grant writing related to machine learning
  • Perform other lab support roles to facilitate research in the lab


Qualifications and Education Requirements

  • PhD in Computer Science, Computer Engineering, or Biomedical Engineering or Equivalent. Master level qualifications will be considered depending on level of experience
  • Experience in maintaining Linux and Windows based computer hardware required
  • Background in machine (deep) learning required
  • Experience with Pytorch or Tensorflow required
  • Background in medical image analysis preferred but not required
  • Technical writing for scientific writing preferred but not required
  • Excellent problem-solving skills
  • Ability to work well with a team and to use initiative in achieving goals

Applications should include curriculum vitae, a brief description of future research interests, as well as contact information for two references.


In accordance with Institute’s policy and legislated health and safety requirements, employment is conditional upon the verification of credentials, completion of a health review, and demonstrating proof of immunity and vaccination status of vaccine-preventable diseases. All employees and affiliates will follow safe work practices and comply with health and safety policies, procedures, and training. Successful candidates will be required to provide two (2) written reference letters from their former employer(s)/supervisor(s).

To ensure the safety and wellbeing of all our people and patients, Sinai Health has made it a priority to support everyone in getting vaccinated against COVID-19. Consistent with this, our Staff Immunization & Surveillance Policy was recently updated to include the requirement for full vaccination – currently defined as receiving two doses and serving a 14-day waiting period following the second dose – in order to be able to work at Sinai Health. To be compliant with our updated Policy, you must provide proof of dual COVID-19 vaccination, as indicated on the Prospective Immunization and Surveillance Policy Information Sheet, in order to be eligible for employment at Sinai Health. If you believe you are one of the very few people who may require an exemption from vaccination, supporting medical information must be submitted to our Occupational Health department, who will review and assess.

We are a fully committed to fairness and equity in employment and our recruitment and selection practices. We encourage applications from Indigenous peoples, people with disabilities, members of sexual minority groups, members of racialized groups, women and any others who may contribute to the further diversification of our Sinai Health community. Accommodation will be provided in all parts of the hiring process as required under our Access for People with Disabilities policy. Applicants need to make their requirements known in advance.

The Lunenfeld-Tanenbaum Research Institute is a scent sensitive environment, and all members of the community are expected to refrain from wearing or using scented products while visiting or working at the Institute. We also support a barrier-free workplace supported by the Institute’s accessibility plan, accommodation and disability management policies and procedures. Should you require accommodation at any point during the recruitment process, including accessible job postings, please contact the Lunenfeld-Tanenbaum Human Resources Department.


Posting open until July 15, 2022. We thank all candidates for applying. Only those selected for an interview will be contacted.

Hours: 37.5 hours per week

Contact Name: Online
Contact Email: Online
Contact Phone: Online


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