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Lead Scientist in Computational Chemistry
3 months ago
Position Overview:
The University of Toronto is seeking a dedicated and skilled Staff Scientist to join the Acceleration Consortium, focusing on the Medicinal Chemistry and Human Organ Mimicry research initiatives. The ideal candidate will possess substantial expertise in machine learning (ML), computational chemistry, and/or computational biology, particularly in the application of these skills to imaging data (e.g., microscopy) and modeling biomolecular interactions (e.g., virtual screening, docking).
Key Responsibilities:
The Staff Scientist will be instrumental in advancing AI-driven autonomous discovery, contributing to the development of materials and molecules essential for addressing significant societal challenges such as climate change and health crises. Responsibilities include:
- Implementing machine learning techniques for SDL development.
- Contributing to SDL and automation projects.
- Providing research direction and oversight.
- Collaborating with a diverse team of scientists and engineers.
Qualifications:
Applicants should hold a Ph.D. in chemistry, materials science, life sciences, physics, engineering, computer science, or a related field. A minimum of five to ten years of experience in accelerated research and development, particularly in machine learning applications within computational chemistry and/or biology, is required. Candidates should also have experience working closely with Principal Investigators or as a Principal Investigator, overseeing lab activities, and collaborating with industry partners.
Desired Expertise:
We are looking for candidates with:
- Strong computational skills in life and physical sciences.
- Proficiency in programming and high-performance computing.
- Experience with programming languages such as Python, MATLAB, C++, and machine learning methodologies.
- Familiarity with chemoinformatics and chemical database software.
The Staff Scientist will work alongside a team of highly skilled researchers, sharing knowledge and expertise to drive innovation in the field of autonomous laboratories. This role is pivotal in shaping the future of materials and molecular discovery.
