Job description

Are you a driven and innovative researcher with a passion for advancing healthcare through cutting-edge AI technology? Join our team and take on the exciting challenge of developing advanced models to integrate multi-modal health data for improved diagnosis and treatment of prostate and kidney cancer in our PhD project!This PhD project is part of the European project ‘Computational Models for patient stratification in urologic cancers – Creating robust and trustworthy multimodal AI for health care – COMFORT‘. The project aims to develop and prospectively validate multimodal, AI-based decision support tools to improve detection, diagnosis and prognosis of patients with prostate cancer (PCa) and kidney cancer (KC).

Background Prostate cancer (PCa) and kidney cancer (KC) are among the most prevalent cancers worldwide. Europe has some of the highest incidence rates of KC for both men and women globally, while PCa accounted for approximately 23% of all new cancer cases diagnosed in men in European Union countries in 2020. These cancers have a significant impact on the health and quality of life of those affected, and place an increasing burden on our healthcare system, with costs exceeding EUR 12 billion each year.

Modern medicine generates a tremendous amount of structured and unstructured data (such as electronic health records, biomarkers, and complex medical imaging) that surpasses human analytical abilities, resulting in inaccurate diagnoses and ineffective treatments. Inefficiently leveraging health data exacerbates these burdens. To address these challenges, the newly launched COMFORT research project is developing a cutting-edge decision support system. The innovative tool will use artificial intelligence (AI) and data-driven insights to assist medical professionals in delivering improved care for people affected by PCa or KC. The research should result in a PhD thesis.

Tasks and responsibilities

Conduct research in the development of multimodal AI for urologic cancer.
Collaborate with a multidisciplinary team to translate cutting-edge technology into clinical practice.
Publish research findings in peer-reviewed journals and present at international conferences.
Mentor junior team members and contribute to the development of the lab’s research direction.

Department

You will work in the Diagnostic Image Analysis Group (DIAG). DIAG is part of the Departments of Imaging, Pathology, Ophthalmology, and Radiation Oncology of Radboud University Medical Center. We develop computer algorithms to interpret and process medical images. The group currently consists of around 70 researchers. Radboud University Medical Center and Radboud University are located in Nijmegen, the oldest Dutch city with a rich history and one of the liveliest city centers in the Netherlands. Radboud University has over 17,000 students. Radboudumc is a leading academic center for medical science, education and health care with over 8,500 staff and 3,000 students.

Radboudumc Radboud university medical center is a university medical center for patient care, scientific research, and education in Nijmegen. Radboud university medical center strives to be at the forefront of shaping the healthcare of the future. We do this in a person-centered and innovative way, and in close collaboration with our network. We want to have a significant impact on health and healthcare. We want to improve with each passing day, continuously working towards better healthcare, research, and education. And gaining a better understanding of how diseases arise and how we can prevent, treat, and cure them, day in and day out. This way, every patient always receives the best healthcare, now and in the future. Because that is why we do what we do.Read more about our strategy and what working at Radboud university medical center means. Our colleagues would be happy to tell you about it. #weareradboudumc

Profile

We are looking for a highly motivated and creative researcher with an MSc degree in Computer Science, Mathematics, Physics, Engineering or a related field who is eager to develop innovative artificial intelligence algorithms in the healthcare domain.In addition, the ideal candidate will possess excellent communication skills and thrive in a collaborative, multidisciplinary team environment. Proficiency in software development, particularly in Python, is a must-have, while experience with deep learning, machine learning, and image analysis or time series analysis is a plus.

Terms of employment

Working at Radboud university medical center means that you are ahead of the curve and working together on the healthcare of the future. And there is more. Our secondary terms of employment are impressive. These are fully tailored to you thanks to our Employment Conditions Selection Model. At Radboud university medical center, you will be given trust, and you will take the responsibility to handle everything together.

A gross monthly salary between € 2.789 and € 3.536 (scale 10A) based on full-time employment.
From 1 November 2023 the wages will increase by 4%.
An annual vacation allowance of 8% and an end-of-year bonus of 8.3%.
If you work irregular hours, you will receive an allowance.
As a full-time employee (36 hours per week), you are entitled to approximately 168 vacation hours (over 23 days) per year.
Radboud university medical center pays 70% of the pension premium. You pay the rest of the premium with your gross salary.
You get a discount on health insurance as well: you can take advantage of two group health insurance plans. UMC Zorgverzekering and CZ collectief.
We provide annual courses, both professional and personal.

In addition to our terms of employment, we also offer employees various other attractive facilities, such as childcare and sports facilities. Want to learn more? Take a look at the CAO UMC.

Application procedure

Will you make a difference for our patients? We would like to receive your application before 6 June 2023. We will then contact you shortly.

What else can you expect?

When you begin employment, we will request a certificate of conduct (VOG) and, depending on the position, you may be screened. You do not need to do anything for this; we will inform you later. Radboud university medical center is an employer that welcomes everyone. Every colleague brings valuable experience, expertise, and creativity. We believe in the benefits of a diverse and inclusive organization. #weareradboudumc

Read more about our application procedure or take a look at the frequently asked questions. We are recruiting for this vacancy ourselves. We only accept applications directly from the applicants themselves, but intermediaries are welcome to share our vacancies in their networks.

Contact

Any questions? Please contact dr. Alessa Hering MSc, Postdoc. Use the Apply button to submit your application.