University of Guelph, Mathematics and Statistics

Position ID: 2877-ASCCA [#20974]
Position Title: Postdoctoral Position in Applied Statistics – Climate Change and Agriculture
Position Type: Postdoctoral
Position Location: Guelph, Ontario N1G 2W1, Canada
Application Deadline: 2022/12/31 11:59PMhelp popup* (posted 2022/10/05, listed until 2022/12/31)
Position Description:    

*** the listing date or deadline for this position has passed and new applications are no longer accepted. ***

Position Title: Applied Statistics – Climate Change and Agriculture Department: Mathematics and Statistics Description of the Area/Topic of Research: The Department of Mathematics and Statistics at the University of Guelph invites applications for a funded post-doctoral position focused on applied statistics and machine learning for assessing the impact of climate change on agricultural productivity in the Canadian and global context. The successful candidate will be involved in the analysis of a myriad streams of environmental and geospatial data recorded on continental scales. This research project is aligned with the objectives of the Food from Thought (FfT) research program at the University of Guelph. The work will be conducted under the supervision of Dr. Khurram Nadeem, who is an FfT affiliated faculty member. General Outline of Duties: Under the supervision of Dr. Khurram Nadeem, the successful candidate will be responsible for leading the research activities of the project, including but not limited to the following: Gathering environmental and geospatial data from various data repositories Restructuring/cleaning large volumes of raw data and conduct exploratory analysis Developing statistical and machine learning models Maintaining data deposition records and documentation Preparing manuscript(s) and presenting findings at research conference(s)

Teaching Requirement: The successful applicant is required to teach a Statistics/Data Science course in the Department of Mathematics and Statistics. Required Qualifications

Candidates must possess a Ph.D. in statistics, mathematical ecology/biology, mathematics, or a related discipline, with a research background in modern statistical learning methods with applications to ecological and/or environmental modeling problems. Prior experience of visualising and analysing large-scale geospatial data using geographic information system software (SAGA GIS/QGIS) is an asset.

In addition to the required qualifications, preference will be given to applicants with:

• Experience in computer programming and statistical computing (C/C++, Python, R); proficiency in Linux

• Experience developing statistical and/or machine learning models for large spatial datasets

• A publication record demonstrating the ability to lead research related to ecological and/or environmental problems

• A demonstrated experience of collecting, integrating, and visualizing various types of spatial and temporal data

• A demonstrated capacity to work independently to accomplish statistical modeling and writing tasks

• Experience working on team research projects

Start Date & Duration of Appointment: Start Date & Duration of Appointment: As soon as possible; 1 year with the potential for renewal subject to satisfactory performance and continued funding.


Application Materials Required:
Submit the following items online at this website to complete your application:
And anything else requested in the position description.

Further Info:
https://mathstat.uoguelph.ca/
519-824-4120 ext. 53136
 
Department of Mathematics & Statistics
50 Stone Road East
MacNaughton Building
University of Guelph
Guelph ON Canada N1G 2W1