Currently Available Positions
Research Associate (S1-RA1), Data scientist and dashboard developer, Building an ecosystem service dashboard for Canada
Start Date: As soon as possible
Salary: $60,000 - $70,000, commensurate with experience,
Duration: 4-5 years (until the completion of ResNet)
Location: Based at McGill’s Macdonald Campus
Supervisors: Dr. Elena Bennett and Dr. Andrew Gonzalez
Project info: http://www.nsercresnet.ca
Description
The RA in this position will work across all landscapes and themes of the project to (a) develop a system to store and manage ResNet data and (b) build and road-test a prototype dashboard using that data to monitor ecosystem services across Canada.
The successful candidate will be responsible for the maintenance, preservation, and sharing of large datasets and tools across ResNet. They will work with all six landscapes and three themes to develop appropriate data storage and metadata standards, as well as to develop instructions about how any ResNet-built tools (e.g., ES models or decision support tools) should be stored to be usable by all in the network. They will also work to ensure that all ResNet data and models are made open source and freely available in an appropriate manner.
The position also has an important research-based component that is focused on using ResNet data to build a prototype dashboard for monitoring ecosystem services at multiple scales. The successful applicant will use generalized models of ecosystem service networks built by the ResNet project team (theme 3), incorporate predictions arising from models of ecosystem service supply and demand (theme 2), and quantitative data and other knowledge forms from across the project’s target landscapes (landscapes 1-6), including decision-space maps (theme 1). This level of integration will ensure that the dashboard is useful to decisions made in Canada’s working landscapes.
Main duties will include:
(a) design and set-up of a data management system (including determining data architecture) that stores and makes accessible landscape level data (in accordance with any ethics requirements of the Universities involved) and models. This data is anticipated to include spatial data (maps of land use/land cover and of the provision of, and demand for, ES), as well as important non-spatial data from each landscape. It is likely to include both quantitative and qualitative data, making for a complex data storage situation. The successful candidate will ensure that this data is organized in a method common and consistent across all six core ResNet landscapes, and accessible to all.
(b) development of a system of metadata to accompany all data in the ResNet database, and explaining/training HQP in the use of this system
(c) maintenance of this data management system, including working with HQP to add new data prior to completion of their degrees.
(d) use of this data and knowledge to build a prototype ecosystem service dashboard for Canadian working landscapes.
Ideal Qualifications
We seek a candidate with a PhD and experience in database management, open science methods, software and dashboard development and programming. Additional valuable skills include top-notch inductive modelling skills, expertise in machine-learning, excellent capacity for synthesis, good people and communications skills to work across the entire project. High level programming skills needed to build a prototype user interface for the dashboard will be extremely valuable. As this person will play a key role in determining appropriate data architecture and storage, a successful candidate must understand data and databases, as well as the nature of the goals of the network. Experience in managing and organizing large, complex datasets with both social and ecological data (including qualitative and quantitative data), as well as experience with dashboard development and programming would be an asset. We will seek a multi-year commitment to this critical synthesis position, aiming to keep one person in the position for the duration of the network if possible.
ResNet recognizes that diversity is central to strong and innovative teams. We encourage candidates to indicate voluntarily on their applications if they are a woman or non-binary gender, an Indigenous person, a person with a disability, or a member of a visible minority group.
To apply:
Please send a cover letter detailing your background and fit to the position, a CV, and a list of three referees to resnet.nrs@mcgill.ca. Please state clearly in the email the position for which you are applying, as we have multiple positions open. Position will remain open until filled. Referees will be contacted for shortlisted candidates only.
Research Associate (S1-RA1), Data scientist and dashboard developer, Building an ecosystem service dashboard for Canada
Start Date: As soon as possible
Salary: $60,000 - $70,000, commensurate with experience,
Duration: 4-5 years (until the completion of ResNet)
Location: Based at McGill’s Macdonald Campus
Supervisors: Dr. Elena Bennett and Dr. Andrew Gonzalez
Project info: http://www.nsercresnet.ca
Description
The RA in this position will work across all landscapes and themes of the project to (a) develop a system to store and manage ResNet data and (b) build and road-test a prototype dashboard using that data to monitor ecosystem services across Canada.
The successful candidate will be responsible for the maintenance, preservation, and sharing of large datasets and tools across ResNet. They will work with all six landscapes and three themes to develop appropriate data storage and metadata standards, as well as to develop instructions about how any ResNet-built tools (e.g., ES models or decision support tools) should be stored to be usable by all in the network. They will also work to ensure that all ResNet data and models are made open source and freely available in an appropriate manner.
The position also has an important research-based component that is focused on using ResNet data to build a prototype dashboard for monitoring ecosystem services at multiple scales. The successful applicant will use generalized models of ecosystem service networks built by the ResNet project team (theme 3), incorporate predictions arising from models of ecosystem service supply and demand (theme 2), and quantitative data and other knowledge forms from across the project’s target landscapes (landscapes 1-6), including decision-space maps (theme 1). This level of integration will ensure that the dashboard is useful to decisions made in Canada’s working landscapes.
Main duties will include:
(a) design and set-up of a data management system (including determining data architecture) that stores and makes accessible landscape level data (in accordance with any ethics requirements of the Universities involved) and models. This data is anticipated to include spatial data (maps of land use/land cover and of the provision of, and demand for, ES), as well as important non-spatial data from each landscape. It is likely to include both quantitative and qualitative data, making for a complex data storage situation. The successful candidate will ensure that this data is organized in a method common and consistent across all six core ResNet landscapes, and accessible to all.
(b) development of a system of metadata to accompany all data in the ResNet database, and explaining/training HQP in the use of this system
(c) maintenance of this data management system, including working with HQP to add new data prior to completion of their degrees.
(d) use of this data and knowledge to build a prototype ecosystem service dashboard for Canadian working landscapes.
Ideal Qualifications
We seek a candidate with a PhD and experience in database management, open science methods, software and dashboard development and programming. Additional valuable skills include top-notch inductive modelling skills, expertise in machine-learning, excellent capacity for synthesis, good people and communications skills to work across the entire project. High level programming skills needed to build a prototype user interface for the dashboard will be extremely valuable. As this person will play a key role in determining appropriate data architecture and storage, a successful candidate must understand data and databases, as well as the nature of the goals of the network. Experience in managing and organizing large, complex datasets with both social and ecological data (including qualitative and quantitative data), as well as experience with dashboard development and programming would be an asset. We will seek a multi-year commitment to this critical synthesis position, aiming to keep one person in the position for the duration of the network if possible.
ResNet recognizes that diversity is central to strong and innovative teams. We encourage candidates to indicate voluntarily on their applications if they are a woman or non-binary gender, an Indigenous person, a person with a disability, or a member of a visible minority group.
To apply:
Please send a cover letter detailing your background and fit to the position, a CV, and a list of three referees to resnet.nrs@mcgill.ca. Please state clearly in the email the position for which you are applying, as we have multiple positions open. Position will remain open until filled. Referees will be contacted for shortlisted candidates only.
NSERC ResNet positions in other labs
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BennettLab Letter to Prospective Students
Photo: Alex Tran
My lab works collaboratively on projects related to understanding the ecology behind ecosystem services management. Ecosystem services such as food, water, soil formation, and erosion control reflect the way in which societies extract resources from the environment. Despite their importance, management of most ecosystem services is poorly understood because it lies in a gray area between natural and social sciences. Many environmental crises, policy debates, and uncertainties in ecosystem management are related to lack of fundamental, empirically-grounded, theoretically consistent information about ecosystem services.
We employ a combination of fieldwork, multi-scale spatial analysis, and modeling to address questions about the provision, use, and management of ecosystem services. To learn more about the work done in my lab, check out the rest of our website. You will find descriptions of my current research interests as well as a list of recent publications, pages for the various students and postdocs involved in the lab, and links to information about graduate school at McGill. The NRS home page and the MSE graduate option page also provide much information relevant to prospective applicants.
I believe that graduate training is one of the most important tasks of a professor, and I tend to invest a lot of time and energy in my students. I am thus very selective in choosing students. I work hard to provide my students with mentoring and advice, space to work, equipment, funding, connections to the broader world of ecology, and a positive lab community. In turn, I expect my students to take an active role in their education and to work hard to do the best work they can do and to make a contribution to ecology, to the lab, and to society. While I spend considerable time with my students, I do not assign topics or projects. Instead, I plan to invest a considerable amount of time helping each student discover their interest and develop their own research questions. While the independent development of a research question can be quite stressful for some students, my opinion is that it is well worth it for the ownership students feel in their projects as a result.
In making decisions about whether to take on a graduate student, I look primarily at three things: the quality and interests of the applicant, the availability of funding, and the current number of students in the lab. In a student, I'm looking for research experience, publications in scientific journals, good grades, passion for science (and life!), and a strong interest in the work we do in the lab. It is not necessary to have all of these, but it helps to have at least a few.
If you are interested in being a student in my lab, please email me a short note introducing yourself, including your CV and an unofficial copy of your academic transcripts (to elena.bennett@mcgill.ca). It helps if you can be fairly specific concerning how your interests overlap mine and what you would be interested in working on during your time at McGill. I look forward to hearing from you!
--Elena
________________________________________________________________________________________________________
KEY INFORMATION
Departmental Deadlines for Application:
Canadian residents and citizens:
Funding sources:
For Canadians and Permanent Residents:
We employ a combination of fieldwork, multi-scale spatial analysis, and modeling to address questions about the provision, use, and management of ecosystem services. To learn more about the work done in my lab, check out the rest of our website. You will find descriptions of my current research interests as well as a list of recent publications, pages for the various students and postdocs involved in the lab, and links to information about graduate school at McGill. The NRS home page and the MSE graduate option page also provide much information relevant to prospective applicants.
I believe that graduate training is one of the most important tasks of a professor, and I tend to invest a lot of time and energy in my students. I am thus very selective in choosing students. I work hard to provide my students with mentoring and advice, space to work, equipment, funding, connections to the broader world of ecology, and a positive lab community. In turn, I expect my students to take an active role in their education and to work hard to do the best work they can do and to make a contribution to ecology, to the lab, and to society. While I spend considerable time with my students, I do not assign topics or projects. Instead, I plan to invest a considerable amount of time helping each student discover their interest and develop their own research questions. While the independent development of a research question can be quite stressful for some students, my opinion is that it is well worth it for the ownership students feel in their projects as a result.
In making decisions about whether to take on a graduate student, I look primarily at three things: the quality and interests of the applicant, the availability of funding, and the current number of students in the lab. In a student, I'm looking for research experience, publications in scientific journals, good grades, passion for science (and life!), and a strong interest in the work we do in the lab. It is not necessary to have all of these, but it helps to have at least a few.
If you are interested in being a student in my lab, please email me a short note introducing yourself, including your CV and an unofficial copy of your academic transcripts (to elena.bennett@mcgill.ca). It helps if you can be fairly specific concerning how your interests overlap mine and what you would be interested in working on during your time at McGill. I look forward to hearing from you!
--Elena
________________________________________________________________________________________________________
KEY INFORMATION
Departmental Deadlines for Application:
Canadian residents and citizens:
- March 15th for September registration
- October 15th for January registration
- January 15th for September registration
- August 15th for January registration
Funding sources:
For Canadians and Permanent Residents:
- FQRNT funding: http://www.fqrnt.gouv.qc.ca/nateq/bourses/
- NSERC funding: http://www.nserc.ca/index.htm
- Fellowships: http://www.mcgill.ca/gps/postdocs/fellowships
Interested students should also look at the following web-sites for information about graduate school at McGill:
http://www.mcgill.ca/nrs/
http://www.mcgill.ca/nrs/graduate/
http://www.mcgill.ca/mse
http://www.mcgill.ca/mse/programs/envroption/