Postdoctoral Research Fellow, Medical Imaging and Machine Learning

3 days ago

Saskatoon SK, Canada University of Saskatchewan Full time
Postdoctoral Research Fellow, Medical Imaging and Machine Learning Postdoctoral Research Fellow, Medical Imaging and Machine Learning

Primary Purpose:

We are seeking an exceptional Postdoctoral Research Fellow to join our interdisciplinary team at the forefront of machine learning, computer vision, medical image analysis, and cardiovascular imaging. This position offers an exciting opportunity to contribute to cutting-edge projects that aim to revolutionize the diagnosis and treatment of cardiovascular diseases through advanced imaging technologies.

Nature of Work:

  • Develop novel machine learning algorithms for the analysis of medical imaging data.
  • Collaborate with a team of clinicians, computer scientists, and engineers to integrate these technologies into clinical workflows.
  • Publish research findings in high-impact journals and present at international conferences.
  • Contribute to the development of grant proposals.

Accountabilities:
The successful candidate will work closely with Dr. Scott Adams, MD, PhD, FRCPC (Principal Investigator) and Dr. Xin Yi, PhD (Senior AI Lead). The candidate will be supported in publishing in top-tier journals and conferences and emphasis will be placed on professional growth and career development. The candidate will have the opportunity to collaborate with colleagues from world-class institutions from around the world. Remote work will be considered.

Education

  • PhD in Computer Science, Electrical Engineering, Biomedical Engineering, or a related field.

Experience:

  • Proven track record of publications in high-impact journals and conferences such as ICML, NeurIPS, CVPR, ICCV, ECCV, MICCAI, and Nature Medicine.

Skills:

  • Strong background in medical image analysis, computer vision, and machine learning.
  • Excellent programming skills in programming languages including Python and experience with machine learning frameworks such as TensorFlow or PyTorch.
  • Proficiency in version control systems, such as GitHub/Git.
  • Excellent communication and collaboration skills.

To Apply:
Please include a cover letter and CV with your application. For any questions, contact: scott.adams@usask.ca . The position will remain open until a suitable candidate is identified.

Department: Medical Imaging
Status: Term 12 months with the possibility of extension
Employment Group: Post-Doctoral Fellows - PSAC
Full Time Equivalent (FTE): Negotiable, up to 1.0 FTE
Salary Family (if applicable):
Salary Phase/Band: Not Applicable
Posted Date: 6/25/2024
Closing Date: open until filled
Number of Openings: 1
Work Location: May be eligible for hybrid work under the terms of USask's Alternative Workspace Guidelines

Postdoctoral Research Fellow, Medical Imaging and Machine Learning

Primary Purpose:

We are seeking an exceptional Postdoctoral Research Fellow to join our interdisciplinary team at the forefront of machine learning, computer vision, medical image analysis, and cardiovascular imaging. This position offers an exciting opportunity to contribute to cutting-edge projects that aim to revolutionize the diagnosis and treatment of cardiovascular diseases through advanced imaging technologies.

Nature of Work:

  • Develop novel machine learning algorithms for the analysis of medical imaging data.
  • Collaborate with a team of clinicians, computer scientists, and engineers to integrate these technologies into clinical workflows.
  • Publish research findings in high-impact journals and present at international conferences.
  • Contribute to the development of grant proposals.

Accountabilities:
The successful candidate will work closely with Dr. Scott Adams, MD, PhD, FRCPC (Principal Investigator) and Dr. Xin Yi, PhD (Senior AI Lead). The candidate will be supported in publishing in top-tier journals and conferences and emphasis will be placed on professional growth and career development. The candidate will have the opportunity to collaborate with colleagues from world-class institutions from around the world. Remote work will be considered.

Education

  • PhD in Computer Science, Electrical Engineering, Biomedical Engineering, or a related field.

Experience:

  • Proven track record of publications in high-impact journals and conferences such as ICML, NeurIPS, CVPR, ICCV, ECCV, MICCAI, and Nature Medicine.

Skills:

  • Strong background in medical image analysis, computer vision, and machine learning.
  • Excellent programming skills in programming languages including Python and experience with machine learning frameworks such as TensorFlow or PyTorch.
  • Proficiency in version control systems, such as GitHub/Git.
  • Excellent communication and collaboration skills.

To Apply:
Please include a cover letter and CV with your application. For any questions, contact: scott.adams@usask.ca . The position will remain open until a suitable candidate is identified.

Department: Medical Imaging
Status: Term 12 months with the possibility of extension
Employment Group: Post-Doctoral Fellows - PSAC
Full Time Equivalent (FTE): Negotiable, up to 1.0 FTE
Salary Family (if applicable):
Salary Phase/Band: Not Applicable
Posted Date: 6/25/2024
Closing Date: open until filled
Number of Openings: 1
Work Location: May be eligible for hybrid work under the terms of USask's Alternative Workspace Guidelines

The University is committed to employment equity, diversity, and inclusion, and are proud to support career opportunities for Indigenous peoples to reflect the community we serve. We are dedicated to recruiting individuals who will enrich our work and learning environments. All qualified candidates are encouraged to apply; however, in accordance with Canadian immigration requirements, Canadian citizens and permanent residents will be given priority. We are committed to providing accommodations to those with a disability or medical necessity. If you require an accommodation to participate in the recruitment process, please notify us and we will work together on the accommodation request. We continue to grow our partnerships with Indigenous communities across the province, nationally, and internationally and value the unique perspective that Indigenous employees provide to strengthen these relationships. Verification of Indigenous Membership/Citizenship at the University of Saskatchewan is led and determined by the deybwewin | taapwaywin | tapwewin: Indigenous Truth policy and Standing Committee in accordance with the processes developed to enact the policy. Successful candidates that assert Indigenous membership/citizenship will be asked to complete the verification process of Indigenous membership/citizenship with documentation. The University of Saskatchewan’s main campus is situated on Treaty 6 Territory and the Homeland of the Métis. We pay our respects to the First Nations and Métis ancestors of this place and reaffirm our relationship with one another. Together, we are uplifting Indigenization to a place of prominence at the University of Saskatchewan.

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