Department/Faculty Summary

The Department of Earth and Atmospheric Sciences at the University of Alberta offers interdisciplinary approaches to diverse teaching and research themes. One of the largest and best supported departments in Canada, it has an international reputation for leading-edge research. Undergraduate programs parallel the research themes and include Environmental Earth Sciences, Geology, Paleontology, Human Geography and Planning.

The Earth and Atmospheric Sciences department was established in 1995 when the former departments of Geology (1912) and Geography (1957) were merged. EAS has more than 50 faculty members, and over 120 graduate students, and is recognized for its scholarly achievement, excellence in teaching and research, and service to the community.

Position Summary

The Department of Earth and Atmospheric Sciences at the University of Alberta invites applications for a tenure track position at the Assistant Professor level in Remote Sensing of the Environment and Machine Learning. Exceptional candidates may be considered for hiring at the rank of Associate Professor. The applicants will make use of our world class facilities and expertise in Earth Observation Sciences via the University of Alberta’s Centre for Earth Observation Sciences (CEOS), and more broadly with existing campus strengths in machine learning. We are seeking an individual who demonstrates the potential to develop a strong research program in remote sensing, and the application of machine learning approaches to earth observation.

Successful candidates will be nominated for a Canada CIFAR Artificial Intelligence (CCAI) Chair by the Alberta Machine Intelligence Institute (Amii). Amii is one of three institutes named in the Pan-Canadian AI Strategy and represents more than 35 artificial intelligence (AI) & machine learning (ML) researchers at the U of A, as well as CCAI Chairs at post-secondary institutions across Western Canada. The CCAI Chair includes research funding for at least five years. This position is part of a University of Alberta cluster hire in the areas of research strength that include Health, Energy and Indigenous Initiatives in health and humanities, among others. The University of Alberta is world-renowned for its strength in AI; this cohort will bring together and foster the next generation of scientists leading the development of machine learning for societal benefit, fulfilling Amii’s mandate of AI for good and all.

Candidates must hold a Ph.D. (or equivalent) in Remote Sensing with emphasis on Machine Learning applications. Areas of interest include (but are not limited to): 1) Object-Based convolutional neural networks (CNNs) and multiview learning for land cover/use classifications, 2) machine learning applied to terrestrial, airborne, and spaceborne LiDAR scanning systems and their point clouds, 3) active learning applied to drone base data sets, and 4) data fusion approaches applied to LiDAR and hyperspectral datasets). Candidates are expected to have demonstrated potential to develop an innovative research program that is externally funded, and to provide high-caliber teaching and mentorship at undergraduate and graduate levels. Evaluation of research potential will be based on the applicant’s record of publications and presentations in high impact venues, research funding record, a summary of planned research projects, and appropriately supportive and detailed letters of reference (to be made available on request after an initial screening of all applications). Teaching and supervisory potential must be documented via previous teaching experiences, reference letters, and a statement of teaching philosophy. Strong potential to collaborate with researchers in the Department and other units of the University of Alberta will be viewed as an asset.

The University of Alberta is one of Canada’s largest post-secondary institutions, and the Department of Earth & Atmospheric Sciences (EAS), with more than 55 faculty, is one of its largest and highest impact Earth Science departments. The University and EAS provide numerous opportunities for collaborative research, and the normal teaching load is 2.5 courses per year. The successful candidates will be expected to develop an innovative and robust externally funded research program, engage in, and develop domestic and international research networks, teach graduate and undergraduate classes, supervise and mentor graduate and undergraduate students, and provide service to the Department, the Faculty, and the University, as well as to professional and external communities.

The University of Alberta is committed to Equity, Diversity and Inclusivity (Strategic Plan for EDI) and to reconciliation (Indigenous Strategic Plan). We welcome applicants from all qualified persons. We encourage women; First Nations, Métis, and Inuit persons; members of visible minority groups; persons with disabilities; persons of any sexual orientation or gender identity and expression; and all who may contribute to the further diversification of ideas and the University to apply.

Interested individuals should submit a curriculum vitae, a description of their area(s) of research and planned research projects; an equity, diversity, and EDI statement that includes the candidate’s contributions and plans to advance EDI in their research, teaching, and service; and a statement of teaching philosophy. Applicants should provide the names and contact information for three individuals who can provide letters of reference.

Inquiries regarding the position can be addressed to the Department Chair, Dr. Stephen T. Johnston, easchair@ualberta.ca.

All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority. If suitable Canadian citizens or permanent residents cannot be found, other individuals will be considered.

Review of applications will begin January 23, 2022 and will continue until the position is filled, with a targeted start date of July 1, 2023.

Minimum Qualifications

Candidates must hold a Ph.D. (or equivalent) in Remote Sensing with emphasis on Machine Learning applications. Areas of interest include (but are not limited to):

1) Object-Based convolutional neural networks (CNNs) and multiview learning for land cover/use classifications,

2) machine learning applied to terrestrial, airborne, and spaceborne LiDAR scanning systems and their point clouds,

3) active learning applied to drone base data sets, and

4) data fusion approaches applied to LiDAR and hyperspectral datasets).

Candidates are expected to have demonstrated potential to develop an innovative research program that is externally funded, and to provide high-caliber teaching and mentorship at undergraduate and graduate levels. Evaluation of research potential will be based on the applicant’s record of publications and presentations in high impact venues, research funding record, a summary of planned research projects, and appropriately supportive and detailed letters of reference (to be made available on request after an initial screening of all applications). Teaching and supervisory potential must be documented via previous teaching experiences, reference letters, and a statement of teaching philosophy. Strong potential to collaborate with researchers in the Department and other units of the University of Alberta will be viewed as an asset.

To assist the University in complying with mandatory reporting requirements of the Immigration and Refugee Protection Act (R203(3)(e)), please include the first digit of your Canadian Social Insurance Number in your application. If you do not have a Canadian Social Insurance number, please indicate this in your application.