- Location
- Stewart Biology Bldg, Canada
- Type
- Part-time
- Department
- Education
- Seniority
- Entry
- Education
- PhD
- Closing date
- Today
- Source
- Workday
Description
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Hiring Unit: Department of Biology (Professor Laura Pollock)
Position Summary:
- Develops and implements species distribution models (SDMs) to predict the geographic distributions of tropical plant species using environmental, climatic, geographic, and biodiversity datasets.
- Compiles, cleans, and integrates large ecological datasets, including plant occurrence records, climate variables, remote-sensing products, topographic data, land-cover data, and other environmental predictors.
- Designs and evaluates statistical and machine-learning approaches for modelling plant species distributions and assessing environmental drivers of tropical forest biodiversity.
- Develops AI/ML methods to improve species distribution predictions, including model training, feature selection, hyperparameter optimization, model comparison, and validation.
- Develops reproducible computational workflows and pipelines for ecological data processing, modelling, visualization, and prediction.
- Analyzes and interprets model outputs in an ecological and evolutionary context and communicate implications for tropical forest biodiversity and conservation.
- Produces figures, maps, statistical analyses, and other research outputs for scientific publications, reports, presentations, and grant applications.
- Prepares manuscripts and contributes to scientific publications, including drafting methods, results, figures, and supplementary materials.
- Collaborates with ecologists, computational scientists, data scientists, and other members of the research team, including external collaborators.
- Provides technical guidance to graduate students and research personnel working on ecological data analysis, modelling, and computational workflows, where appropriate.
Qualifications:
- Strong programming skills in R and/or Python.
- Ability to develop reproducible computational workflows and maintain well-documented code.
- Strong data visualization and scientific communication skills.
Education/Experience:
- PhD in Ecology, Biology, Ecology & Evolution, Environmental Science, Computer Science, Data Science, Computational Biology, or a closely related field.
- Experience coordinating a large and diverse set of collaborators.
- Demonstrated research experience applying computational or quantitative methods to ecological or biological questions.
- Demonstrated experience developing and applying species distribution models, ecological niche models, or related spatial/statistical models.
- Experience working with large ecological, environmental, biodiversity, or geospatial datasets.
Location: This position is located in Montreal, Quebec and the work for this position is expected to be performed in Quebec.
Knowledge of French and English: McGill University is an English-language university where day to day duties may require English communication both verbally and in writing. The level of English required for this position has been assessed at a level # (4) qualifier on a scale of 0-4.
Hourly Salary:
Hours per Week:
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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].
