Research Associate

Updated: 9 days ago
Job Type: FullTime

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Department of Biology

Project Title: CANBON pilot: Operationalization of Tools and Models for Ecosystem Services in Hudson Bay Lowlands

Position Summary:

The Gonzalez is seeking a Research Associate to join a dynamic research group to support the development and application of monitoring and modelling tools for ecosystem services. The recruited candidate will work closely with institutional partners at Environment and Climate Change Canada, GEO BON, and Quebec Centre for Biodiversity Science. The Hudson Bay Lowlands are composed of complex and dynamic landscapes dominated by wetlands, including open and forested bogs and peat plateaus, fens, and swamps, marshes, and open water. These landscapes support multiple ecosystem services, including regulating services such climate regulation, water regulation and flood reduction. The HBL is a persistent sink of atmospheric carbon dioxide that has contributed significantly to cooling the global climate. The region provides traditional food and food security to the region’s indigenous peoples (e.g., freshwater fisheries, foraging wild foods). It is also an important cultural landscape for spiritual, hunting, and recreational activities. Mapping and modeling ecosystem services in this region is a current research challenge.

Duties:

  • Combine biodiversity, ecosystem, climate, social data using analytical tools and models to detect and attribute change in ecosystem services;

  • Conducts a thorough review and assessment of methods (e.g. essential ecosystem service variables).

  • Proposes a suite of tools that can be scaled for implementation of ecosystem service assessments in Canada, including biodiversity, climate change mitigation and traditional knowledge and values.

  • With the existing datasets, operationalizes the application of assessment tools to data from the Hudson Bay Lowlands. The focus will be on methods that allow for the inclusion and effective analysis of a broad range of data types, that can weave data and information on biodiversity, carbon storage and sequestration, and Indigenous knowledge, in particular knowledge on culturally important species and species important for food security.


Qualifications:

  • Conception of a data to model workflow, linking multiple sources of biological and ecological information across scales to monitor and model ecosystem and biodiversity change.

  • Advanced skills in statistical programming and modeling.

  • Geospatial data analysis.

  • Familiarity with ecosystem models.

  • Development of an integrated modelling workflows using Python, Julia and/or R.

  • PhD in related field

  • 5years experience following PhD (PhD received prior to 2019)

  • Strong computational and environmental modelling background

  • 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 3 (qualifier) on a scale of 0-4.


Hourly Salary:


$31.20


Hours per Week:


35 (Full time)


Location:


Stewart Biology Bldg


Supervisor:


Professor


Position Start Date:


2024-03-21


Position End Date:


2026-03-31


Deadline to Apply:


2024-04-19

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] .



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