Open Postdoctoral Positions
Our lab is seeking motivated postdoctoral researcher for the Fall 2019 with a strong background in machine learning to push the state-of-the-art in machine learning. Our lab is focused on making a differences in the major challenges arising in health and health care. Researchers will have the potential to participate in and create projects that target basic, translational science that bring novel machine learning techniques towards meaningful applications.
We have offices in the Department of Computer Science at the University of Toronto, and at the Vector Institute. A successful candidate will work on foundational machine learning challenges, leading projects, and collaborating with other researchers. Machine learning topics of interest include, but are not limited to, probabilistic modeling, representation learning, deep learning, time-series modelling, generative models, integrating multi-modal data, model interpretability, convex and non-convex optimization.
These topics are inspired by the challenges posed by biomedical data: high-dimensional, multi-modal datasets with missing data, collected under noisy and imperfect conditions, with complex temporal dynamics and a sensitive nature.
Interested postdoc applicants should have a Ph.D. in machine learning, fairness, applied causality, RL, or statistics with a strong publication record in top conferences such as NeurIPS, ICML, ICLR, AISTATS, AAAI, KDD, AMIA, MLHC, FAT*, etc.
Prior experience working on health-related data is not required, but you must be interested in meaningful applications of your work.
Candidates should send a research proposal, a CV and a cover letter/personal statement including the names of three referees to Dr. Marzyeh Ghassemi and use “ML4H Postdoc Application” in the subject line.
Open Research Assistant Positions
Our lab is seeking a research assistant with a strong strong organizational and technical skills to help manage the ML4H lab's research targets. Researchers assistants will be focused on assisting with project management and planning.
Interested research assistants applicants should have both a BS (or MS) in machine learning or a related technical field, as well as strong writing and organizational skills.
Candidates should send a CV and a cover letter/personal statement including the names of three referees to Dr. Marzyeh Ghassemi and use “ML4H RA Application” in the subject line.
Applying for PhD/MSc
MSc and PhD students apply to the Department of Computer Science at The University of Toronto, indicate your interest area is Machine Learning and Mention Marzyeh Ghassemi as a PI of interest. Note that we receive a large volume of applications, and the pool is very competitive.
Our group is proud to host scholars, students, and professionals to work on important health problems with machine learning. We are the best fit for those who want to build and deploy machine learning models, often with an emphasis on health.
We value a diverse and inclusive team, and believe that the lab environment should be an intellectual safe space for contributors of different backgrounds and viewpoints.
You should either have a strong machine learning background, or strong development background.
- Machine Learning: A good candidate should have background in math, specifically probability and linear algebra, and ideally some AI/ML coursework (optional).
- Development: A good candidate should have a background in collaborative software projects, specifically developing in corporate software systems or significant open source contributions.
Volunteers should contact the lab with a resume (and transcript if a student) and a 2-3 paragraph description of what you would like to be involved with. Volunteers are expected to spend a minimum of 20 hours per week on their project. The large volume of applicants may cause delays in our response time.
University of Toronto Student Volunteers
- We expect this project to be your primary academic activity outside of coursework, and will prioritize those who can be involved for at least two terms.
Non-Toronto Student Volunteers
- You must have independent work authorization. We are not able to sponsor visas nor take on volunteers that want to work remotely.
- We expect volunteers to available for at least 12 weeks of research, and will prioritize those who can be involved for longer.