Assistant researcher to the Diagnostic Radiology research group

Description of the workplace
The Diagnostic Radiology research group conducts research related to clinical medical imaging. LUCI (Lund University Cancer Imaging) is an interdisciplinary group of researchers and healthcare professionals with a primary focus on innovative clinical imaging methods in breast cancer diagnostics, particularly the use of artificial intelligence[DM1] -based breast cancer screening. The group is based at Skåne University Hospital (SUS) in Malmö. Both Diagnostic Radiology and LUCI are led by Professor Sophia Zackrisson and comprise researchers from diverse professional backgrounds as well as technical staff. More information is available here.
Magnus Dustler, Associate Professor of Radiology, conducts research in several areas, including the application of artificial intelligence in breast imaging. In collaboration with the newly established Hybrid Intelligence group at LUSEM, led by Senior Lecturer Blerim Emruli, as well with the collaboration of Professor Dagmar Monett Diaz from HWR Berlin (Berlin School of Economics and Law), we are currently investigating how the use of AI as a decision-support tool affects radiologists’ learning and skills development.
Within the research group, we are committed to fostering a positive working environment characterized by mutual respect and consideration. We strive to create a workplace that is both stimulating and supportive of professional development for all team members. We continuously work to provide favorable conditions for job satisfaction, growth, and participation. We are dedicated to ensuring both physical safety and a healthy psychosocial work environment.

What We Offer

Lund University is a public authority, which means that you are entitled to special benefits, generous annual leave, and a favorable occupational pension.
Read more on the University’s website about being employed at Lund University:
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Work duties and areas of responsibility
As an Assistant Researcher, you will be responsible for conducting a study on how AI tools for mammography image interpretation are used, and how they should be used, in education and clinical practice. The study consists of three components:
A literature review of different strategies for the use of AI in radiology and breast imaging, as well as how the use of AI in other fields has influenced learning and skills development.
A practical image interpretation experiment in which medical students are recruited and trained to interpret mammography images either with or without the support of AI tools. The same students will subsequently review mammography images with or without AI assistance. A particular focus will be the effect of false-positive and false-negative cases.
A practical study in which experienced radiologists review images where AI support is presented in different ways, in order to investigate how the presentation of information affects interpretation performance.

Qualifications

The following qualifications are required for the position:
PhD in Medical Radiation Physics, Medical Image Analysis, Radiology, or a closely related relevant field.
Experience in image perception studies.
Excellent proficiency in spoken and written English
Great emphasis will be placed on personal qualities. The position requires a focused, attentive individual with a broad interest in medical imaging, high-impact research and interdisciplinary collaboration
Meritorious for the position is:
Previous practical or theoretical experience in Hybrid Intelligence.
Experience in machine learning, particularly in applications related to medical imaging, both in research and clinical settings.
Experience in breast imaging research.
Experience in image analysis and image management using relevant programming languages (e.g., Python, MATLAB, or similar).
Experience in educational research, particularly within medical education.
Proficiency in spoken and written Swedish.

Additional Information

This is a secial fixed-term employment (SÄVA) for a 12 months period with preliminary starting date 2027-02-01, or according to agreement. 100 %.

How to Apply

Applications must be submitted through the University’s recruitment system. The application should include a cover letter describing how you meet the qualification requirements and why you are interested in the position. The application should also include a CV, a copy of your doctoral degree certificate, and any other documents you wish to submit in support of your application (such as copies of degree certificates and academic transcripts, contact details for referees, letters of recommendation, etc.)