Postdoctoral Fellow - Machine Learning in Medicine
Competition 845

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Department Faculty of Science - Computing Science
Posted date April 24, 2024
Closing date Will remain open until filled.
Position Type Full Time

Description

This position has an end date of May 31, 2026, and offers a benefits package found at Postdoctoral Fellows Benefits.

Location - This role can be in-person, hybrid, or remote.

Working at the University of Alberta

The University of Alberta acknowledges that we are located on Treaty 6 territory, and respects the histories, languages and cultures of First Nations, Métis, Inuit and all First Peoples of Canada, whose presence continues to enrich our vibrant community.

The University of Alberta is a community of knowledge seekers, change makers and world shapers who lead with purpose each and every day. We are home to more than 14,000 faculty and staff, over 40,000 students and 260,000 alumni worldwide.

Your work will have a meaningful influence on a fascinating cross-section of people — from our students and community members, to our renowned researchers and innovators, making discoveries and generating solutions that make the world healthier, safer, stronger and more just. Learn more.

Working for the Department of Computing Science

Founded in 1964, the Department of Computing Science at the University of Alberta is the oldest and one of the largest computing science departments in Canada. We have an international reputation for contributions in the many fields of computing, both in foundations and applications. The Department currently consists of 51 faculty members, approximately 326 graduate students, 20 post-doctoral fellows and research associates, 1,352 undergraduate students and 12 administrative staff. Our research partners come from a wide variety of industries and other academic disciplines.

Position 

We are looking for a talented, knowledgeable and ambitious candidate to research several interesting medical-informatics tasks related to epidemiology (population disease forecasting) and bio-chemical analysis, as well as foundational topics, especially survival prediction and counterfactual reasoning, towards effectively learning personalized treatment effects. You will be working with the Greiner Lab at the University of Alberta & the Alberta Machine Intelligence Institute (Amii).

Duties 

  • Participate in relevant research and direct several projects
  • Work with (and perhaps co-supervise) various students
  • Collaborate with many colleagues, in both machine learning and medicine/healthcare
  • (Co)write high-impact scientific publications
  • Present your work at leading conferences
  • Develop tools that can be used by researchers and practitioners

Qualifications

  • PhD in computing science or a related area, with a focus on machine learning and statistics
  • Evidence of high-quality research, such as publications in relevant top-tier venues
  • Effective communicator in English, both written and spoken
  • Experience in Medical Informatics is an asset  

Application Instructions:

Please submit your curriculum vitae, list of publications, references, and cover letter. Please ensure that your cover letter summarizes your past work and insights on medical informatics and outlines specific future directions.

At the University of Alberta, we are committed to creating an inclusive and accessible hiring process for all candidates. If you require accommodations to participate in the interview process, please let us know at the time of booking your interview and we will make every effort to accommodate your needs.

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.

We thank all applicants for their interest; however, only those individuals selected for an interview will be contacted.

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, M├ętis 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.

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