Machine Learning Scientist - Toronto - Oncoustics

    Oncoustics
    Oncoustics Toronto

    1 week ago

    Description

    Overview

    Machine Learning Scientist (Graduate/Postdoc Level) - Contract at Oncoustics

    We're seeking a graduate student or postdoc in machine learning who's eager to gain hands-on experience at a cutting-edge healthtech startup. You'll collaborate closely with leading professors, experienced scientists and developers, and successful entrepreneurs. An immediate start is preferred, with full-time availability through the summer. Part-time or flexible arrangements are also welcome.

    TORONTO — CONTRACT

    Location

    Toronto, ON (Hybrid work at our Toronto Office, 155 Queens Quay East)

    Responsibilities

    • Design, build, and debug new neural network architectures from scratch
    • Adapt and optimize existing deep learning models for challenging data cases
    • Diagnose and interpret model limitations using performance metrics
    • Work with regression and classification models, including waveform/time-series signals and imbalanced datasets
    • Implement strategies for individual frame-to-patient data aggregation
    • Contribute to end-to-end ML pipelines, including training and evaluation
    • Apply methods such as multi-instance learning, self-supervised learning, or contrastive learning

    Requirements

    • Experience in coding, ideally Python and MATLAB

    Good to have

    • Experience with ultrasound data or related domains (e.g., audio, non-destructive testing, geophysics)
    • Ideally based in Toronto for Hybrid work at our Toronto Office, 155 Queens Quay East
    • Familiarity with clinical data workflows or biomedical applications
    • Motivated, driven, collaborative, and eager to learn and produce real-world results

    Application

    Submit Your Application — Resume

    Note: Upload status and file details have been simplified from the original posting. You will be prompted to upload your resume during the application process. If you encounter issues, please try again or contact support.


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