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Faculty Position in Computing: Computational Intelligence

Queen’s University

January 2026

The School of Computing at Queen’s University invites applications for a faculty position at the rank of Assistant or Associate Professor that centres on Computational Intelligence. The preferred start date for the appointment is January 1, 2026.

 Qualifications

Candidates must have a PhD or equivalent degree completed at the start date of the appointment. The successful candidate will provide evidence of high-quality scholarly output that demonstrates a track record of independent research leading to high-quality peer assessed publications and the securing of external research funding, as well as strong potential for outstanding teaching contributions at both the undergraduate and graduate levels, and an ongoing commitment to academic and pedagogical excellence in support of the department’s programs. Candidates must provide evidence of an ability to work collaboratively in an interdisciplinary and student-centred environment. The

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Research Opportunities

Computer Vision

Work description

Implement the selected methods for automatic scoring of the aesthetic result of the treatment for breast cancer. Write the activity report on the fellowship.

Academic Qualifications

Be enrolled in a doctoral program in Electrical and Computer Engineering, Informatics, or similar.

Minimum profile required

Global score in the master of at least 15 out of twenty.

Preference factors

Experience in Python. Experience in computer vision.

Maintenance stipend: € 1309.64, according to the table of monthly maintenance stipend for FCT grants , paid via bank transfer. Grant holders may be awarded potential supplements, according to a quarterly evaluation process (Articles 19, 21 and 22 of the Regulations for Grants of INESC TEC and Annex II), up to a maximum limit of 50% of the monthly maintenance stipend.

INESC TEC supports costs with registration,

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Research Opportunities

Electrical, Informatics, Biomedical Engineering

Work description

Extend the knowledge of the state of the art in machine learning for generation of artificial data. Extend the knowledge of the state of the art in machine learning for multimodal data fusion. Identify and select the appropriate methods for the study in question. Develop the research capacity through the application of the selected methods. Exercise a critical spirit in the evaluation of the research process and the results obtained.

Minimum profile required

Experience in Computer Vision and machine learning.

Preference factors

Experience in research projects.

Maintenance stipend: € 1309.64, according to the table of monthly maintenance stipend for FCT grants , paid via bank transfer. Grant holders may be awarded potential supplements, according to a quarterly evaluation process (Articles 19, 21 and 22 of the Regulations for Grants of INESC

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