Every day, clinics worldwide generate vast amounts of digital data on healthy and diseased individuals. Digital pathology alone, with its high-resolution imaging of tissue samples, provides wealth of large-scale data that can contribute to improved understanding of disease morphology and tissue phenotype, potentially providing new insights to help clinicians treating patients in their decision-making process. Will you help us?

Artificial Intelligence has been developed in the past decade to build computational models to translate the wealth of such large-scale data into tools that can be used by. Computational Pathology (CPATH), the field of applying AI to digital pathology image data, has shown how AI can achieve or even surpass human performance at diagnostic tasks such as metastasis detection in lymph nodes, prostate and breast cancer grading and beyond. But despite the rise of highly accurate AI-based computational pathology models, only a few of them are being applied in clinical practice.

In this project, we will investigate and optimize the process of adopting AI CPATH models in the clinic, focusing on clinicians’ needs in clinical decision making when diagnosing and treating cancer patients. Within the context of a KWF-funded project, we will use CPATH models for breast cancer digital pathology as a use case and focus on their use in informing pathologists and oncologists on personalized treatment plans. We will also develop case studies based on demo installations of AI models in clinical practice to evaluate its implementation and performance in a setting close to clinical practice.

We are looking for a PhD candidate to work within a KWF-funded project, aimed at validating aimed at creating validatinged computational pathology algorithms for improved risk-prediction in breast cancer patients, while preparing the roadmap towards clinical implementation. If you are passionate about these disciplines and want to grow in a stimulating international academic environment, you might be our new colleague!

During your PhD trajectory, you will evaluate the decision-making process in clinical practice and create a framework on how these pathology algorithms can be optimized to aid clinicians. Moreover, with this framework you will provide input and will help with the application and validation of the AI models established by the pathology department. Lastly, you will provide support on the implementation and will evaluate the use of these models in clinical practice.

You are:

• A creative and enthusiastic researcher with a master’s degree in (technical )medicine and preferably with a few years of experience as a clinician (e.g., residencies).
• A person with a clear interest to work with AI algorithms and that has an affinity with improving clinical decision making, an interest in pathology is a plus.
• Has an interest in performing research and analyzing data using statistics.
• Having experience (in modelling) with AI is a plus.
• Someone with good oral and written communication skills in both English and Dutch.

Fixed-term contract: 4 years.

At Radboud university medical center, you build on your future. We are committed to providing the best care, education, and research. And we are true to our word, because we help you develop and seize opportunities and give you the room to grow. As an employer, we believe that employees should feel vital and happy at work in all stages of life. We are also committed to creating a healthy and safe working environment. Our employment conditions contribute to that. What we offer:

• Upon commencement of employment, you will start at scale 10A, step 0 (€ 3.017 based on a full-time appointment). Over a maximum period of 4 years, you will progress to scale 10A, step 3 (€3.824 based on a full-time appointment). You will also receive an 8% holiday allowance, an 8.3% end-of-year bonus, and a 47% to 72% bonus for working unsocial hours.
• 172 vacation hours per year based on a 36-hour working week. (As of 1 January 2025, you will receive 176 vacation hours).

Radboudumc

The Computational Pathology Group (CPG) is a research group of the department of Pathology of the Radboud University Medical Center (Radboudumc). The CPG develops, validates and deploys novel medical image analysis methods, usually based on the newest advances in machine learning with a focus on computer-aided diagnosis (CAD). Application areas include diagnostics and prognostics of breast, colon, prostate and lung cancer. Our group is among the international front runners in the field, witnessed for instance by the highly successful CAMELYON, PANDA and TIGER grand challenges which we organized. The CPG is also part of the cross-departmental Diagnostic Image Analysis Group (DIAG) at Radboudumc, with researchers in the departments of Radiology and Nuclear Medicine, Pathology and Ophthalmology.

The Biostatistics Research Group (BRG) is part of the IQ Health department. The core activities of the BRG are Research, Education and Consultancy. The research themes involve mathematical and statistical techniques to address research questions that range across various disciplines, such as clinical research in rare diseases, clinical trial designs and dynamics of infectious diseases. The application of AI in clinical practice is one of its emerging topics for research. The BRG has a joint leadership role in the development of the Master Medical Data Science, where inferential statistics and epidemiology meet the new developments in deep learning and AI.

Radboudumc
Welcome to Radboud university medical center (Radboudumc), where scientific breakthroughs are born through the curiosity and passion of our collaborating researchers in a vibrant environment. We believe trust and excitement are crucial elements to achieving our goals, and we approach our research as teams and with the utmost rigor to make a significant impact on health and healthcare. Our researchers are driven by their fascination with the biological, psychological, and sociological mechanisms underlying health and healthcare. They collaborate with partners from all over the world to improve health outcomes for all. Radboudumc unites patient care, research, education, and corporate learning, which allows us to approach our mission to shape the health and healthcare of the future in an innovative and person-centered way.

Our ambition is to lead the way in the pursuit of prevention, sustainability, meaningful care. We believe that through our research, we can significantly improve the health and well-being of society. Join us on our mission to make a difference in healthcare. Become a part of our community of gifted researchers, professionals or patient partners who are dedicated to making a real impact on population health and healthcare.

Read what it is like to do a PhD at the Radboud University Medical Center.

Any questions? Or wondering what it is like to work at Radboudumc? Then call, send a message or email to prof. Jeroen van der Laak via +(31)6 15 89 16 07. Use the Apply button to submit your application.