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PhD candidate 'AI-assisted Prostate Ultrasound'

4 years


One in eight men is confronted with prostate cancer (PCa). The current diagnostic trajectory has many shortcomings. The Prostate-Specific Antigen (PSA) blood test has too many false alarms, causing unnecessary biopsies and missing treatable clinically significant PCa (csPCa). Ultrasound (US) guided biopsies are inadequate as a follow up to the PSA test. Due to their unreliability, these biopsies frequently result in either overdiagnosis or underdiagnosis, complicating treatment decisions. As a result, early detection is unfeasible, and prostate cancer is often detected only at a late, possibly fatal stage. Research into timely, accurate, widely available diagnostic modalities is therefore crucial.

Recently, multiparametric magnetic resonance imaging (mpMRI) has evidenced clinical value in reducing unnecessary biopsies. However, MRI is costly and requires expertise both during reading and biopsy. Current MRI-US fusion biopsy improves over US-guided biopsies but still face difficulties. New technology research can result in a breakthrough. Firstly, novel US parameters show increased diagnostic accuracy, evidencing the potential for multiparametric US (mpUS) to become a valuable, cost-effective option for diagnosis and biopsy guidance. Secondly, artificial intelligence (AI) is emerging as a powerful tool to enhance medical image interpretation and reduce diagnostic and interventional workflow and costs. However, the current rise of mpMRI and MRI guided ultrasound provides a solid basis for generating ground truth data of csPCa presence to train and explore AI methodology.

Prognostic Imaging of prostate Cancer by Ultrasound (PICUS) is a recently awarded NWO project that leverages these novel mpUS advances and AI assistance to predict the presence, location, and aggressiveness of PCa. PICUS is led by the Technical University Eindhoven (prof. Massimo Misschi) in collaboration with Radboudumc and various other public and private partners: Canon Medical, General Electric, Angiogenesis Analytics, Martini Klinik Hamburg, Prostaatkanker Stichting. The Radboudumc team will focus on developing AI assisted fusion of mpMRI and mpUS extending upon our state of the art mpMRI AI.

The AI has three purposes: (1) to expand mpMRI in its ability to characterize lesions in order to improve specificity; (2) to improve biopsy targeting by fusing mpUS and mpMRI. (3) to act as standalone detection of prostate cancer on mpUS as a cost-effective alternative to mpMR.

In this project, you will collaborate with the clinical biopsy team in the urology clinic at Radboudumc and set up a data acquisition pipeline. You will link ultrasound and MRI data and expand our collection of reference standard meta-parameters. You will investigate advanced machine learning methods for end-to-end training on ultrasound images, research uncertain AI, and explore the usages of foundation models. You will work together with international partners in the PICUS consortium. You will work with over 80 PhDs in the DIAG group and present results at international meetings.


Our new PhD candidate is a highly motivated, creative, and enthusiastic researcher with an MSc degree in Computer Science, Data Science, Physics, Mathematics, Engineering, or equivalent. You have a thorough understanding of deep learning and can adapt deep learning algorithms. Good knowledge of image processing and ultrasound is highly desirable.

The research should result in a Ph.D. thesis, requiring you to have good communication skills to excel at presenting results at scientific meetings and in scientific journals.


The research group of Professor Huisman is part of the Department of Radiology of the Radboud University Medical Center (Radboudumc). The lab is also part of the cross-departmental Diagnostic Image Analysis Group (DIAG) at Radboudumc, with researchers in other departments, such as Radiology and Nuclear Medicine, Pathology.

We develop, validate and deploy 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 PICAI Camelyon and Panda grand challenges which we organized.

Radboudumc strives to be a leading developer of sustainable, innovative, and affordable healthcare to improve the health and wellbeing of people and society in the Netherlands and beyond. This is the core of our mission: To have a significant impact on healthcare. To get a better picture of what this entails, check out our strategy.

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.


  • 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.) 
  • An Employment Conditions Selection Model, allowing you to use part of your employment conditions to your choosing. For example, you can use your gross salary to purchase additional vacation hours or hours for providing informal caregiving. Or, for example, you can use your gross end-of-year bonus to purchase a bicycle, so you pay less tax.
  • Plenty of opportunities for personal development. You can take a variety of courses in our online learning environment. 
  • Your well-being and vitality are a priority. For example:
    • Save time for work-life balance leave. 
    • A 40% discount on a sports membership of the Radboud Sports Center.
    • Healthy Professionals program to help you manage your energy. 
    • Company Support Team and a personal coach if you are going through a life-changing event.
    • Financially beneficial working less through a Generation Scheme as you approach state pension age.
  • Support in achieving a good work-life balance at every stage of your life. Examples:
    • Advice and courses on, for example, 'Millennial dilemmas' and 'Your Career After 57'.
    • Activities at our own mindfulness center.
    • Informal caregiving consultations if you have questions about juggling work and caregiving responsibilities at home.
  • In addition to statutory pregnancy and maternity leave, Radboud university medical center offers 26 weeks of parental leave, nine of which are paid. In addition, as a partner you can take a maximum of five weeks of supplementary partner leave. During supplementary partner leave and parental leave, we supplement the UWV benefit up to 100% of your salary.
  • Do you wear Radboud university medical center clothing at work? You will receive a dressing allowance of €80 gross per month (fulltime employment contract). 
  • Pension accrual at the ABP Pension Fund. Radboud university medical center pays 70% of the pension premium. 
  • Discounts on supplementary packages of two group health insurances and ten other types of insurance, from home insurance to legal assistance.
  • As of 1 October 2024: an allowance for your commuting costs of € 0.18 per km up to a maximum of 40 km one way. If you use public transport to commute, we will fully reimburse the public transport costs (2nd class). If you regularly work from home, you will receive a working from home allowance of € 2.35 per day.

Opmerkingen en contactinformatie

Any questions? Or wondering what it is like to work at Radboudumc? Then email to Dr. Ir. Henkjan Huisman, associate professor/research group leader. Use the Apply button to submit your application.