TORONTO - CONTRACT
Job Description
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.
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 MATLABGood 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 EastFamiliarity with clinical data workflows or biomedical applicationsMotivated, driven, collaborative, and eager to learn and produce real-world results#J-18808-Ljbffr