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PhD candidate 'Development of conventional and AI-based methods for mammographic image analysis to optimize breast cancer screening’

Development of conventional and AI-based methods for mammographic image analysis to optimize breast cancer screening.In this project, we will develop new …

12 dagen geleden

Arbeidsvoorwaarden

Standplaats:
Geert Grooteplein Zuid, Nijmegen, Gelderland
Dienstverband:
Tijdelijk contract / Tijdelijke opdracht
Uren per week:
36 - 36 uur
Salarisindicatie:
€ 2422 - € 3103 per maand
Opleidingsniveau:
WO

Functieomschrijving

Development of conventional and AI-based methods for mammographic image analysis to optimize breast cancer screening.

In this project, we will develop new artificial intelligence-based and conventional image analysis methods, leveraging recent advances in deep learning and in AI-based automated interpretation of medical images, to optimize the breast cancer screening image interpretation process. Automated AI-based systems can now interpret mammography images with similar performance to that of screening breast radiologists. However, more work is needed before they can have a real and optimal impact on large, regional and national screening programs, like the Dutch National Breast Cancer Screening Programme.

Developing and combining new methods to analyze the images, both in search of lesions but also for interpretation of the tissue patterns present, and their impact on human interpretation, will allow for having a real and impactful influence on the performance of breast cancer screening. This, in turn, will allow for an increase in the early detection of cancer, while reducing the rate of false alarms. As a result, we envision that screening will become more effective and efficient.

The AXTI (Advanced X-ray Tomographic Imaging) laboratory of the Department of Radiology and Nuclear Medicine at Radboudumc works closely with breast screening radiologists and industry to develop new, and improve existing, methods and processes in screening and clinical breast imaging. Our direct connection with the Dutch Expert Centre for Screening (LRCB) ensures and maximizes the relevance and applicability of our developments.

In addition, in this project we will work together with experts in human visual perception, AI-based interpretation of images, AI-based and conventional image analysis methods, and breast cancer screening. We will also work closely with industrial partners that are involved in every aspect of breast cancer image interpretation in screening, including AI, image analysis, and image display and workflow companies.

Tasks will consist of development of novel AI and conventional image analysis methods to optimize the incorporation of AI into breast cancer screening, as well as presenting and writing papers on the study results.

Functie-eisen

  • You should be a creative and enthusiastic researcher with a MSc degree in artificial intelligence, physics, mathematics, medical physics, biomedical engineering, or similar.
  • Experience or interest in radiology and/or medical imaging and affinity with biomedical research.
  • Experience in programming in Python (and preferably other languages, like C++).
  • Excellent communication skills in English, both written and spoken.

Conditions

Upon commencement of employment we require a certificate of conduct (Verklaring Omtrent het Gedrag, VOG) and there will be, depending on the type of job, a screening based on the provided cv. Radboud university medical center's HR Department will apply for this certificate on your behalf.

Read more about the Radboudumc employment conditions and what our International Office can do for you when moving to the Netherlands.

Additional information

Application
The following should be included in your application: CV, letters of recommendation, list of completed courses and grades, a letter of motivation, and reprints or, preferably, links to your thesis or any scientific publications or reports in English that you have written.

Information
All additional information about the vacancy can be obtained from Dr. Ioannis Sechopoulos, Associate Professor. Use the Apply button to submit your application.

Please apply before 28 May 2020.
Recruitment agencies are asked not to respond to this job posting.

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