- Location
- Burnside Hall, Canada
- Type
- Part-time
- Department
- Education
- Education
- PhD
- Closing date
- Today
- Source
- Workday
Description
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Hiring Unit:
Department of Mathematics and Statistics
Position Summary:
- Develop methods for uncertainty quantification and calibration to ensure reliable predictions and risk control.
- Oversees and assists with the design of active-learning strategies and experiments to improve data efficiency and guide experimental decisions.
- Develop and maintain Python pipelines for statistical modelling, experimentation, and analysis.
- Contribute to scientific publications, conference presentations, and grant reporting.
- Develop verifiable retrieval and memory methods for scientific large language model (LLM) agents.
Qualifying skills:
- A PhD in Statistics, Electrical Engineering, Materials Science, Mechanical Engineering, or a related field, with research experience in AI or machine learning, is an asset.
- Knowledge of machine learning, probabilistic modelling, uncertainty quantification, and model interpretability.
- Experience in machine-learning-guided materials design or optimization, demonstrated through peer-reviewed publications.
- Proficiency in Python and scientific machine-learning tools, including reproducible research software development.
Experience and Education:
- A PhD in a related field is an asset.
Before applying, please note that to work at McGill University, you must be both authorized to work in Canada and willing to work in the province of Quebec at the campus where the position is based / located.
McGill University is an English-language university where most teaching and research activities are conducted in the English language, thereby requiring English communication both verbally and in writing. The level of English required for this position has been assessed at a level # 4 on a scale of 0-4.
Hourly Salary:
Hours per Week:
Location:
Supervisor:
Position Start Date:
Position End Date:
Deadline to Apply:
This position is covered by the Association of McGill University Research Employees (AMURE) collective agreement.
McGill University hires on the basis of merit and is strongly committed to equity and diversity within its community. We welcome applications from racialized persons/visible minorities, women, Indigenous persons, persons with disabilities, ethnic minorities, and persons of minority sexual orientations and gender identities, as well as from all qualified candidates with the skills and knowledge to productively engage with diverse communities. McGill implements an employment equity program and encourages members of designated groups to self-identify. Persons with disabilities who anticipate needing accommodations for any part of the application process may contact, in confidence, [email protected].