Machine Learning to improve organ transplant long term success - QC-696Project type: Research
Desired discipline(s): Epidemiology / Public health and policy, Life Sciences, Medicine, Microbiology / Immunology
Project Length: 4 to 6 months
Preferred start date: As soon as possible.
Language requirement: Flexible
Location(s): Québec, QC, Canada
No. of positions: 3 to 5
Desired education level: Master's
Open to applicants registered at an institution outside of Canada: Yes
About the company:
BI Expertise is company based in Quebec, with offices in Quebec City and Montreal. We are specialised in artificial intelligence systems and in collaborative research and innovation. We develop technical solutions leveraging machine learning and new systems architectures to help companies and societies tackle their most pressing challenges in building a better future. We also offer strategic and technical support to integrate artificial intelligence technologies, and integration services of machine learning- or cloud-based solutions. Our expertise spans from systems architecture (cloud, hybrid, edge, etc.) to machine learning, augmented reality with real-time inferences, to blockchain technologies, that we apply to use cases where AI brings a competitive edge in a variety of industries (insurance, security and defence, health, aerospace, etc.).
Describe the project.:
BI Expertise is currently developing a solution to help in improving organ transplants’ long-term success rates thanks to artificial intelligence technologies. For that purpose, we are using machine learning techniques and survival analyses to predict the potential success of a given donor-recipient match over various periods of time. The ultimate goal of this project is to develop a clinical decision support tool for medical teams and organ recipient patients or their families, to help them make informed decisions when evaluating a replacement organ that is proposed to them by organ procurement organisations (Transplant Québec, BC Transplant, Trillium Gift of Life, etc.). The candidate will work with our data science team to support the fine tuning of the machine learning models pertaining to the specific organ(s) that is (are) the object of their research. To that end, they will be conducting a review of the literature on organ transplant and machine learning relating to the specific organ(s) they are working on, as well as various data engineering experiments. The objective of the internship is to support us in selecting the best parameters to provide the most reliable predictions.
We are looking for a graduate candidate in health sciences who is willing to get involved in research and development in an enterprise context. If they are not already, they should be open to becoming familiar with academic research in the field of organ donation and transplantation, and more specifically to develop or deepen an expertise in the following organs: kidneys, heart, lungs, liver, pancreas or islet. The candidate should be familiar with the manipulation of large datasets and have some skills in relating programming languages (Python, R, SQL, etc.) and softwares (MatLab, Anaconda, Jupyter Notebooks, etc.).