Machine Learning Resident - Client: Zamplo (1 Year)
Machine Learning Resident - Client: Zamplo (1 Year)
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Job Description
Join us for a unique ML Resident role focusing on improving patient outcomes by predicting risk of an adverse event leading to an emergency room visit using ML/DL. Youll work in a fast-paced and dynamic team of machine learning scientists healthcare providers and domain experts.
- Soumik Farhan Machine Learning Scientist
Description
About the Role
This is a paid residency that will be undertaken over a twelve-month period with the potential to be hired by our client afterwards. The resident will be reporting to an Amii Machine Learning Scientist and regularly consult with the Client team to share insights and engage in knowledge transfer activities.
About our Client
Zamplo is a digital health company transforming the way individuals clinicians and researchers engage with health data. Its connected health platform empowers people to track and share their own health information while providing real-time insights that support better care and outcomes. Zamplo develops innovative patient-centered tools that reduce costs and improve collaboration across the healthcare system.
The Zamplo platform offers two complementary products:
- Zamplo App: Allows patients to track symptoms medications routines and share information with their care team. It helps patients better manage their health and prepare for meaningful conversations with providers.
- Zamplo Research: An electronic data capture platform designed for researchers clinicians and organizations. With patient consent it enables collection of patient-reported outcomes and wearable data supports electronic consent and streamlines data management to advance clinical research and improve care delivery.
About the Project
The project aims to use machine learning to classify a patients risk of an adverse event leading to an emergency room visit following radiation therapy. This risk assessment will use socio-demographic non-medical and medical data. By identifying patients with a higher risk of an adverse event earlier patients healthcare providers caregivers and community stakeholders can implement proactive measures to improve patient outcomes.
As research in this specific area is limited the resident would approach the classification problem in a number of ways each with its own set of experiments and models to determine the best option to implement. Following model development the results will be externally validated in both retrospective and prospective manners.
Required Skills / Expertise
Were looking for a talented and enthusiastic individual with solid knowledge of machine learning experience working with health care data and a passion to improve individual health outcomes.
Key Responsibilities:
- Utilize a range of supervised unsupervised methods to build a robust and deployable predictive model.
- Ingest and understand (including performing exploratory data analysis and baseline statistical assessments) medical data from multiple patient health data sources.
- Experiment and fine-tune the model(s) as necessary based on the performance of baseline and deployment expectations.
- Collaborate with the project team and domain experts to iteratively develop models and define identified health event outcomes.
- Implement model explainability and interpretability techniques to provide insights to patients and clinicians.
- Participate in regular meetings with the client and stakeholders preparing presentations and reports.
- Research and implement different approaches to the problem from literature as well as publicly available tools.
Required Qualifications:
- Completion of a Computer Science (or a related graduate degree program) MSc. or PhD with specialization in predictive health or medical applications.
- Proficient in developing and training fine-tuning and evaluating machine learning and deep neural network models in PyTorch and/or TensorFlow.
- Proficient in Python programming language and related ML frameworks libraries and toolkits.
- Solid understanding of classical statistics and its application in model validation.
- Familiarity with Linux Git version control and writing clean code.
- A positive attitude towards learning and understanding a new applied domain .
- Must be legally eligible to work in Canada.
Preferred Qualifications:
- Familiarity with and hands-on experience with medical and/or health data.
- Publication record in peer-reviewed academic conferences or relevant journals in machine learning.
- Experience/familiarity with software engineering best practices.
- Experience using cloud platforms (GCP AWS Azure etc.)
Non-Technical Requirements:
- Desire to take ownership of a problem and demonstrated leadership skills.
- Interdisciplinary team player enthusiastic about working together to achieve excellence.
- Capable of critical and independent thought.
- Able to communicate technical concepts clearly and advise on the application of machine intelligence.
- Intellectual curiosity and the desire to learn new things techniques and technologies.
Why You Should Apply
Besides gaining industry experience additional perks include:
- Work under the mentorship of an Amii Scientist for the duration of the project.
- Participate in professional development activities.
- Gain access to the Amii community and events.
- Get paid for your work (a fair and equitable rate of pay will be negotiated at the time of offer).
- Build your professional network.
- The opportunity for an ongoing machine learning role at the clients organization at the end of the term (at the clients discretion).
Location: Alberta Preferred
About Amii
One of Canadas three main institutes for artificial intelligence (AI) and machine learning our world-renowned researchers drive fundamental and applied research at the University of Alberta (and other academic institutions) training some of the worlds top scientific talent. Our cross-functional teams work collaboratively with Alberta-based businesses and organizations to build AI capacity and translate scientific advancement into industry adoption and economic impact.
How to Apply
If this sounds like the opportunity youve been waiting for please dont wait for the closing September 22 2025 to apply - were excited to add a new member to the Amii team for this role and the posting may come down sooner than the closing date if we find the right candidate before the posting closes! When sending your application please send your resume and cover letter indicating why you think youd be a fit for your cover letter please include one professional accomplishment you are most proud of and why.
Applicants must be legally eligible to work in Canada at the time of application.
Amii is an equal opportunity employer and values a diverse workforce. We encourage applications from all qualified individuals without regard to ethnicity religion gender identity sexual orientation age or disability. Accommodations for disability-related needs throughout the recruitment and selection process are available upon request. Any information provided by you for accommodations will be kept confidential and wont be used in the selection process.
Employment Type
Full-Time
