Full Time Faculty Assistant / Associate Professor in Applied Machine Learning (ML)/Artificial Intelligence (AI) in Land Use Science

Full Time Faculty Assistant / Associate Professor in Applied Machine Learning (ML)/Artificial Intelligence (AI) in Land Use Science

ALES Dean’s Office General

Competition No. - A108449460D1 Closing Date - Will remain open until filled.

The Faculty of Agricultural, Life and Environmental Sciences (ALES) invites applications for an Assistant Professor tenure-track position in Applied Machine Learning (ML)/Artificial Intelligence (AI) in Land Use Science . Exceptional candidates may be considered for hiring at the rank of Associate Professor  The ALES vision is to support one AMII (Alberta Machine Intelligence Institute) Land Use Science Chair with a research focus in the complementary areas of agriculture and forestry which may encompass plant and animal breeding/genomics, cropping systems, soil health, forest tree breeding/genomics, land use, climate change, and agri-food processing optimization. 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)  and machine learning (ML) researchers at the UofA, as well as CCAI Chairs at post-secondary institutions across Western Canada. The CCAI Chair includes research funding for a minimum of five years. This position is part of a UofA cluster hire in the areas of research strength that include Health, Energy and Indigenous Initiatives in health and humanities, among others. The UofA is world-renowned for its strength in AI; this new cluster hire 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. The ML/AI CIFAR Chair will support the integration and application of these technologies into Faculty teaching and research in forestry and agriculture. More specifically, this Chair may develop research on the use of diverse temporal and spatially explicit data to support precision management of agricultural and forestry commodities, optimization of food processing using complex, continuous flow big data, and provide the foundation to inform policy at provincial and national levels. In addition, ALES envisions this ML/AI Chair will have collaborative linkages to other proposed Chairs within this AMII cluster hire, which include Remote Sensing (Science) and Space (Science/Engineering).  Other research areas, focused on advanced optimization techniques for resource allocation and reinforcement learning to support agriculture/forestry industries and the development of coupled biophysical-economic policy models, will also be a priority. This ML/AI Chair will manage and exploit the ever-increasing data flows in production systems in agriculture and forestry (including bioenergy products), expanding Alberta’s capacity to excel in these future-focused fields of study.  The position will be a joint appointment across two ALES departments, Renewable Resources (RENR) and Agricultural, Food and Nutritional Sciences (AFNS), with linkages to the Department of Resource Economics and Environmental Sciences (REES). There will be opportunities to collaborate with the Faculties of Science and Engineering, also located within the College of Natural and Applied Sciences, and with other groups across campus. Minimum Qualifications: Candidates must hold a Ph.D. (or equivalent) in Agricultural, Forestry or Land Use Science with an emphasis on Machine Learning and/or Artificial Intelligence applications. Areas of interest include (but are not limited to): the application of cyber-physical systems for improved logistics; sustainability, or product quality improvement; optimized, real-time agronomic management; advancing genomics-based research on plant breeding and improving soil health; incorporating genomics approaches to improve forest growth and yield; enhanced system sustainability through climate and land use characterization and prediction; designing of improved processes and decision tools using computational strategies and data streaming; and application of machine learning adapted from other industries that bring productivity and sustainability improvements to agriculture, forestry, policy and conservation. Salary will be commensurate with qualifications and experience and includes a comprehensive benefits package and professional expense allowance. 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 Faculty and other units of the University of Alberta will be viewed as an asset. Interested individuals should submit a curriculum vitae, a cover letter, a description of their area(s) of research and planned research program; an equity, diversity, and inclusivity statement that includes the candidate’s contributions and plans to advance EDI in their research, teaching, and service; and a teaching statement (including a teaching philosophy, summary of courses taught and/or course material, and any available evaluation materials). Applicants should provide the names and contact information for three individuals who can provide letters of reference. Applications will be accepted until a suitable candidate is found. Candidates who previously applied do not need to re-apply. 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. The records arising from this competition will be managed in accordance with provisions of the Alberta Freedom of Information and Protection of Privacy Act (FOIPP).

How to Apply

Note: Online applications are accepted until midnight Mountain Standard Time of the closing date.

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. The University of Alberta is committed to an equitable, diverse, and inclusive workforce. We welcome applications 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 those who may contribute to the further diversification of ideas and the University to apply.