Registered Nurse, Orthopedic clinic

SickKids; Toronto; On-site; CAD 60,000 - 80,000; Full time

Job summary

SickKids is seeking a Machine Learning for Drug Discovery Post-Doctoral Research Fellow to develop ML-based pipelines for drug discovery. The role involves interdisciplinary collaboration to create generative models aimed at enhancing healthy human lifespan. Candidates should have a PhD in a relevant field and strong programming skills in Python.

Benefits

Access to dedicated computational resources

High bandwidth in supervision

Interdisciplinary environment with ML, chemistry, and biology

Qualifications

• Strong publication track record in top ML or computational biology conferences.
• Experience in drug discovery and chemical data is preferred.
• Hands-on experience in developing and training deep learning models.

Responsibilities

• Develop generative models for small molecule design.
• Contribute to interdisciplinary research bridging ML with chemistry.
• Collaborate with biologists and chemists at SickKids.

Skills

Python

Deep Learning

Generative Models

Reinforcement Learning

Education

PhD in machine learning-related discipline

Tools

PyTorch

JAX

Job description

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Machine Learning for Drug Discovery Post-Doctoral Research Fellow

Position Description

The position is under the supervision of Dr. Michal Koziarski within the Molecular Medicine program at the Hospital for Sick Children and Vector Institute. Our research group focuses on developing machine learning-based pipelines that leverage generative models and active learning to efficiently explore chemical space, with applications in anti-aging intervention discovery. We seek a candidate interested in fundamental ML research driven by real-world applications and aligned with the goal of extending healthy human lifespan.

The role will center on developing generative models for small molecule design and applying them to various longevity-related projects, including (but not limited to) the discovery of novel senolytics. The candidate will contribute to the development of novel methods that integrate ML with chemistry, emphasizing cost and speed of chemical synthesis. While we specialize in computer science and algorithm development, our goals go beyond just improving benchmark results - we're focused on designing new therapeutics that help people live longer, healthier lives. As a result, our research is highly interdisciplinary, bridging ML with experimental work and fostering close collaborations with biologists and chemists at SickKids, the University of Toronto, and the Acceleration Consortium.

• Contract length: 1 year, with the possibility of extension

What We Offer:

• An interdisciplinary environment with expertise and close collaborations spanning core ML, chemistry, and biology.
• ML research fundamentally motivated by the most pressing biological questions.
• Flexibility in shaping research directions in alignment with the group's mission and the candidate's interests.
• High bandwidth in supervision: as a newly established group, we have the capacity to closely support and mentor the successful candidate.
• Access to dedicated computational resources at SickKids Research Institute and the Vector Institute cluster.
• Engagement with the Vector Institute and Acceleration Consortium ecosystems.

Requirements:

• PhD in a machine learning-related discipline.
• Strong publication track record in top ML, computational chemistry, or computational biology conferences and journals.
• Proficiency in Python, demonstrated through completed projects, preferably with publicly available repositories.
• Experience with deep learning frameworks such as PyTorch and JAX.
• Hands-on experience in developing and training deep learning models.
• Familiarity with reinforcement learning and/or generative models.

Preferred Qualifications:

• Experience in drug discovery and chemical data.
• Background in generative models for small molecule design.
• Experience with GFlowNets.
• Familiarity with active learning approaches.

Prospective candidates are encouraged to reach out directly to Dr. Michal Koziarski to discuss potential research directions at [e-mail].

Our Commitment to Diversity

SickKids is committed to championing equity, diversity and inclusion in all that we do, fostering an intentionally inclusive and culturally safe environment that reflects the diversity of the patients, families and communities we serve. Learn more about workplace inclusion.

Accessibility & Accommodation

If you require accommodation during the application process, please reach out to our aSKHR team . SickKids can provide access and inclusion supports to eligible candidates to support their full engagement during the interview and selection process as well as to ensure candidates are able to perform their duties once successfully hired. If you are invited for an interview and require accommodation, please let us know at the time of your invitation to interview. Information received related to access, inclusion or accommodation will be addressed confidentially.

How To Apply

Technical difficulties? Email [e-mail] with a short description of the issues you are experiencing. We will not accept resumes sent to this inbox but we are happy to respond to requests for technical assistance.

Tip:Combine your cover letter and resume intoONEdocument of 20 pages or less as you cannot upload multiple documents as part of your application.