2 Vacancies for AI - researchers on smart breast MRI

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Function description


Breast MRI has proven to be an excellent technique for the early detection of breast cancer. For this purpose, a standard MRI protocol is generally used that can be used for both detection and classification of abnormalities. Nevertheless, this standard protocol is not optimal for all women. 


In this project, you will work on the development of an AI application that can directly analyze the MRI and can be used for optimization and individualization of the scan protocol.

You will conduct this research within the Breast Imaging Group (BIG). BIG is a multidisciplinary research group with the mission to combat breast cancer through the development and optimization of radiological techniques for detection and treatment. BIG connects the NKI/AvL and the Radboudumc. The NKI/AVL is a leading comprehensive cancer center with a very strong international reputation in the field of breast cancer treatment. Radboudumc is a university hospital that has been leading for decades in the field of AI development for applications in breast radiology. There is a very close collaboration with the AI for oncology group within the AvL. In this project there is also a collaboration with the VUmc.
In this project you will work together with a multidisciplinary team consisting of specialists in the development of artificial intelligence for medical imaging, MR physicists and breast radiologists. The project is funded by KWF cancer foundation.


The project has room for 2 full-time researchers with an inherent drive to improve breast cancer care. 


Position 1 focuses on the development and implementation of automatic detection algorithms for lesions on breast MRI. In doing so, you will not only be concerned with the optimization of already existing AI algorithms, but also develop (web-based) applications that make the output of the models available to lab technicians and radiologists very quickly.


Position 2 focuses on the development of AI algorithms that can work directly with the k-space data generated by the MR scanner. You will be involved in the development of fast reconstruction techniques for undersampled data and the development of high-sensitivity detection algorithms for breast cancer on MRI.


Job requirements
You are an enthusiastic, motivated, and talented researcher with the desire to obtain a PhD (postdoc is also a possibility).


For Position 1, we are looking for a researcher with a master's degree in computer science, physics, (technical) medicine or similar. You are driven to transform theoretical algorithms into practical applications and to provide evidence that this can be used to improve care. Experience in the development and implementation of AI algorithms and/or web-based applications is recommended.


For Position 2, we are looking for a researcher with a master's degree in physics, mathematics, computer science or similar. Your drive lies in the development of image reconstruction and processing tools. You have extensive knowledge of the physical basis of MRI acquisitions and standard and advanced image reconstruction techniques. Experience in the development of AI algorithms for image reconstruction is a plus.


Compensation
The basis for your employment conditions is in accordance with the CAO hospitals on the basis of a 36-hour work week. As the research group is spread between Amsterdam and Nijmegen you are free to choose your place of employment.

Interested?
For further information about this vacancy please contact Dr. Ritse Mann (mammaradiologist) on 020 512 1728 and/or Dr. Jonas Teuwen (group leader AI for oncology).

Applications for this vacancy can be submitted until Monday, August 30. 
Applications will be considered for the duration of the vacancy. We aim to respond to your application within 2-3 weeks.

The NKI values diversity and is committed to creating an inclusive work environment that stimulates the best in each individual. Applications of all individuals are welcomed regardless of age, ancestry, religion, disability, distance from the labor market, sexual orientation or gender identity.


Acquisition in response to this vacancy is not appreciated.