Part-time Project management Offres d'emploi - Sault Ste. Marie, ON

Research Associate (Limited Term) (2 Year Term, 40% FTE)

Date Posted : 02 / 14 / 2025

Req ID : 41662

Faculty / Division : Faculty of Applied Science & Engineering

Department : Department of Electrical & Computer Engineering

Campus : St. George (Downtown Toronto)

Description

The Edward S. Rogers Sr. Department of Electrical & Computer Engineering is Canada’s top-ranked ECE department, and one of the largest. We are home to 100 active and Emeritus professors, more than 1,400 undergraduate and 800 graduate students. Many of our faculty members are world leaders in their field and have been recognized as the brightest and most promising scientists and engineers across the country.

The evolution of cloud-native platforms and software-defined infrastructures has introduced a new paradigm for autonomous service orchestration, resource management, scalable infrastructure, and smart application deployment. This project aims to advance orchestration frameworks, intelligent workload management, and adaptive resource provisioning in large-scale, distributed environments. The selected candidate will be supervised by Prof. Alberto Leon-Garcia.

The research will explore the design and development of autonomous orchestration frameworks for next-generation computing, emphasizing multi-cloud environments, decentralized service orchestration, and autonomous system management across various use cases. By integrating real-time stream processing, analytics, and machine learning approaches, the project seeks to optimize service and infrastructure performance, enhance security, and enable intelligent decision-making throughout the lifecycle of cloud-native applications.

Responsibilities

As part of the Network Architecture Lab (NAL), the Research Associate will :

• Design and develop orchestration, analytics, and machine learning algorithms for heterogeneous resource management, autonomous infrastructure control, and adaptive workload scaling.
• Implement intelligent workload scheduling, predictive scaling mechanisms, and event-driven automation for cloud-native platforms.
• Develop software-defined resource provisioning systems using real-world data from multi-cloud infrastructures and smart environments.
• Optimize the performance and scalability of orchestration frameworks for large-scale distributed computing.
• Contribute to research publications, technical reports, and open-source frameworks in software-defined platforms, autonomous computing, and intelligent cloud-native architectures.

Qualifications

A Ph.D. in Computer Science, Computer / Network Engineering, or a related field (or nearing completion) with a robust research foundation in cloud-native computing, distributed systems, machine learning–driven orchestration, and software-defined infrastructure. The ideal candidate should demonstrate both theoretical expertise and practical experience, and possess :

Required Documents

Candidates are requested to submit a comprehensive cover letter that summarizes the research experience of the applicant and a CV.

Please Note : This is a 2 year term position at 40% FTE.

Closing Date : 02 / 25 / 2025, 11 : 59PM ET

Employee Group : Research Associate

Appointment Type : Grant - Term

Schedule : Part-Time

Pay Scale Group & Hiring Zone : R01 Research Associates (Limited Term) at 40% FTE : $21,029 - $39,430

Job Category : Engineering / Technical

All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.

Diversity Statement

The University of Toronto embraces Diversity and is building a culture of belonging that increases our capacity to effectively address and serve the interests of our global community. We strongly encourage applications from Indigenous Peoples, Black and racialized persons, women, persons with disabilities, and people of diverse sexual and gender identities. We value applicants who have demonstrated a commitment to equity, diversity and inclusion and recognize that diverse perspectives, experiences, and expertise are essential to strengthening our academic mission.

As part of your application, you will be asked to complete a brief Diversity Survey. This survey is voluntary. Any information directly related to you is confidential and cannot be accessed by search committees or human resources staff. Results will be aggregated for institutional planning purposes. For more information, please see http : / / uoft.me / UP .

Accessibility Statement

The University strives to be an equitable and inclusive community, and proactively seeks to increase diversity among its community members. Our values regarding equity and diversity are linked with our unwavering commitment to excellence in the pursuit of our academic mission.

The University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA). As such, we strive to make our recruitment, assessment and selection processes as accessible as possible and provide accommodations as required for applicants with disabilities.

If you require any accommodations at any point during the application and hiring process, please contact uoft.careers@utoronto.ca .

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