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    Technical Specialist - Toronto, ON, Canada - University Health Network

    University Health Network
    University Health Network Toronto, ON, Canada

    1 week ago

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    Description

    Company Description

    The University Health Network, where "above all else the needs of patients come first", encompasses Toronto General Hospital, Toronto Western Hospital, Princess Margaret Cancer Centre, Toronto Rehabilitation Institute and the Michener Institute of Education. The breadth of research, the complexity of the cases treated, and the magnitude of its educational enterprise has made UHN a national and international resource for patient care, research and education. With a long tradition of ground-breaking firsts and a purpose of "Transforming lives and communities through excellence in care, discovery and learning", the University Health Network (UHN), Canada's largest research teaching hospital, brings together over 16,000 employees, more than 1,200 physicians, 8,000+ students, and many volunteers. UHN is a caring, creative place where amazing people are amazing the world.

    Job Description

    Union: Non-Union
    Site: Toronto General Hospital
    Department: UHN Digital
    Reports to: AI Hub Lead
    Work Model: Hybrid
    Grade: H0:08
    Hours: 37.5 hours per week
    Salary: $43.37 to $54.21 hourly
    Shifts: Monday to Friday
    Status: Temporary Full Time (1 year)
    Closing Date: May 31, 2024

    Position Summary
    We are looking for a Technical Specialist with health care and Dev Ops experience to join our University Health Network (UHN) Collaborative Centre for Artificial Intelligence (AI) and Data Science to work with the cancer program. The UHN AI Hub brings together scientists and clinicians from across UHN working to develop and implement safe and responsible applications of AI to improve health care. This role involves working in close collaboration with care providers, researchers and students to build deep expertise and support the MLOps of advance novel applications of artificial intelligence methods to facilitate research and translation into clinical practice.

    The Technical Specialist will design and develop highly sophisticated ML pipelines, deployment platforms and methodologies to support high priority initiatives with cutting edge AI technology within the UHN network. The Technical Specialist works closely with the Chief AI Scientist and team to apply MLOps methods to solve complex health related questions, improve hospital efficiency and develop new research hypotheses. Primary responsibilities include, but are not limited to deploying, managing and optimizing machine learning models in production environments to ensure smooth integration and efficient operations. The Technical Specialist will collaborate with oncology clinicians and scientists to build data pipelines and securely deploy responsible AI. The Technical Specialist will possess strong technical proficiency, creativity, and strong collaborative skills to contribute towards furthering AI capacity and innovation within UHN.

    Duties

    Data Processing and Pipelines: Creating and building robust data pipelines for AI. Working with large datasets of oncology data. This involves preprocessing, cleaning, and organizing data for data pipelines and AI integration.

    Model Implementation and Management: Develop and deploy AI models in a clinical environment. This could include creating new data pipelines and integrating AI models into existing clinical systems and processes. Set up monitoring tools to monitor AI performance and track various metrics such as response time, errors and resource utilization.

    Algorithm Optimization: Work with data science specialists to fine-tune algorithms for deployment.

    Collaborative Research: Work closely with biologists and clinicians to understand their data needs and translate these into computational tasks.

    Publishing and Documentation: Regularly document your findings and methodologies. Publish in peer-reviewed journals and present at conferences.

    Grant Writing: Assist in writing grant proposals for funding research projects.

    Mentoring and Supervision: Guide junior researchers or students in their projects, providing expertise in oncology data analysis.

    Qualifications

    • Undergraduate degree, graduate would be an asset, in engineering, computer science, or related disciplines.
    • Minimum 5 years related experience required.
    • Excellent communication skills and ability to utilize a collaborative approach to solving challenging problems.
    • Experience with MLOps, enterprise application development, implementing and maintaining ML and NLP models, IT administration and support.
    • Experience with Python (scikit-learn, Pandas, etc.) and deep learning frameworks (TensorFlow or PyTorch)
    • Experience with healthcare data types, topics, and scientific challenges and approaches.
    • Familiarity with HPC environment and running applications in HPC clusters.
    • Demonstrate ability to mentor others and work collaboratively with clinicians.
    Additional Information

    Why join UHN?

    In addition to working alongside some of the most talented and inspiring healthcare professionals in the world, UHN offers a wide range of benefits, programs and perks. It is the comprehensiveness of these offerings that makes it a differentiating factor, allowing you to find value where it matters most to you, now and throughout your career at UHN.
    • Competitive offer packages
    • Government organization and a member of the Healthcare of Ontario Pension Plan (HOOPP
    • Close access to Transit and UHN shuttle service
    • A flexible work environment
    • Opportunities for development and promotions within a large organization
    • Additional perks (multiple corporate discounts including: travel, restaurants, parking, phone plans, auto insurance discounts, on-site gyms, etc.)
    Current UHN employees must have successfully completed their probationary period, have a good employee record along with satisfactory attendance in accordance with UHN's attendance management program, to be eligible for consideration.

    All applications must be submitted before the posting close date.

    UHN uses email to communicate with selected candidates. Please ensure you check your email regularly.

    Please be advised that a Criminal Record Check may be required of the successful candidate. Should it be determined that any information provided by a candidate be misleading, inaccurate or incorrect, UHN reserves the right to discontinue with the consideration of their application.

    All UHN Employees are required to be fully vaccinated with a COVID-19 vaccine series, approved by Health Canada or the World Health Organization, as a condition of hire. Proof of COVID-19 vaccination will be required. Should you be the successful candidate, you will be required to comply with UHN's mandatory Vaccination Policy that is in effect.

    UHN is an equal opportunity employer committed to an inclusive recruitment process and workplace. Requests for accommodation can be made at any stage of the recruitment process. Applicants need to make their requirements known.

    We thank all applicants for their interest, however, only those selected for further consideration will be contacted. #J-18808-Ljbffr
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