Data Scientist - Generative and Agentic AI

We are a team of highly experienced and collaborative bioinformatics scientists and we are seeking a qualified contractor to help us evaluate and develop generative AI and agentic AI approaches for healthcare and computational biology applications.

Your work will involve research and development of generative AI and agentic AI based methods for multiple bioinformatics domains, including next-generation sequencing (NGS), precision medicine and related biological data workflows. Working at the intersection of state-of-the-art AI and bioinformatics will provide the opportunity to apply advanced AI methods to important real-world biomedical problems.

Job Duties/Responsibilities:
Review and assess the state of the art in generative AI and agentic AI with an emphasis on biological and healthcare applications.
Assist in the design, development and evaluation of models and workflows involving generative AI and agentic AI for bioinformatics applications, including next-generation sequencing and precision medicine.
Propose and assess strategies for training, benchmarking and improving these models and workflows.
Implement methods and algorithms using Python and other relevant libraries and frameworks.
Validate the accuracy, robustness and performance of the developed models, tools and workflows.
Ensure that all work is well tested, documented and reproducible.
Prepare clear technical summaries of methods, results and recommendations.
Collaborate with scientists and engineers to support delivery of project milestones.


Qualification/Experience Required:
Enrollment in or recent completion of a Masters degree or PhD in a quantitative field such as mathematics, physics, computer science, information science, bioinformatics or a related discipline.
Proficiency in Python programming is required.
Experience working in a Unix-like environment is required, including use of remote or high performance computing environments.
Experience in applied machine learning, including traditional machine learning and deep learning using PyTorch or similar frameworks.
Experience with experimental design, benchmarking and performance evaluation of machine learning models is desired.
Background in statistics, probability theory and/or linear algebra is desired.
Knowledge of generative AI, large language models and/or agentic AI methods is a plus.
Knowledge of biological data analysis, bioinformatics and/or biology is a plus.


Mandatory Skills Required:
Enrollment in or recent completion of a Masters degree or PhD in a quantitative field such as mathematics, physics, computer science, information science, bioinformatics or a related discipline.
Proficiency in Python programming is required.
Experience working in a Unix-like environment is required, including use of remote or high performance computing environments.
Experience in applied machine learning, including traditional machine learning and deep learning using PyTorch or similar frameworks.

Nice to Have Skills Required:
Background in statistics, probability theory and/or linear algebra.
Knowledge of generative AI, large language models and/or agentic AI methods.
Knowledge and experience in analyzing biological data and/or biology.

Top Primary Goals for New Hire within 60days:
Complete a focused review of relevant literature and propose an initial technical plan for selected generative AI and agentic AI use cases in bioinformatics.
Deliver an initial prototype or benchmark workflow in Python for at least one defined biological data application.
Establish a reproducible development and evaluation setup, including code organization, documentation and initial performance results.


Work Location: This is an onsite role within the Mississauga Campus. Candidate will be required to work onsite at least 3 days every week.