Vacancy PhD candicate 'Towards clinical implementation of AI for oncological dermatopathology'

Job description

Due to the tripling of skin cancer incidence over the past two decades, more skin biopsies and resections are performed than ever before. This has led to an enormous increase in workload for pathologists, who perform the microscopic diagnostics of skin samples. The biopsy and the resection need to be inspected by a pathologist, each typically consisting of multiple glass slides. Due to the increased incidence of skin cancer and the number of patients undergoing skin biopsies, the amount of work for pathologists has risen to unprecedented levels.

At the Radboudumc, at least 25% of all diagnostic tissue samples are now skin neoplasia, of which most are non-melanoma skin cancers. Of these, basal cell carcinomas increased tenfold in the last twenty years. The increased workload is even worse in peripheral pathology labs that directly receive diagnostic material from GPs and primary care dermatologists. With the expected further increase in the incidence of skin cancer, this will become even more problematic in the future. Most microscopic skin analysis is not professionally challenging, but it is time-consuming and can lead to reduced time for more complex diagnostics and increased patient wait time. Machine learning, specifically deep learning, offers a path to automating the diagnoses of skin samples, reducing the pressure on pathologists and the cost of diagnosis, both in time and money.

We have developed an existing AI algorithm that can identify and subtype basal cell carcinomas, the most common skin cancer, with high accuracy. However, this algorithm must defer the long tail of more dangerous diseases to a pathologist using out-of-distribution detection to allow reliable automated triaging. Furthermore, the most time-consuming part of BCC diagnostics is the reporting, which needs to be added using vision-language modeling.

Tasks and responsibilities

• Develop effective and reliable out-of-distribution detection methods for histopathological diagnosis. Integrate language and image models to produce interpretable AI-generated reports.
• Work together with industry representatives and local IT to implement AI systems in the pathology IMS 4. Collaborate with pathologists and (inter)national researchers to validate your developed algorithms in large cohorts.
• ave fun interactions with colleagues, present at local and (inter)national conferences, and develop yourself as an independent researcher.

Place of work

The Computational Pathology Group is a research group of the department of Pathology of the Radboud University Medical Center (Radboudumc). We are 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.

We develop, validate and deploy novel medical image analysis methods, usually based on deep learning technology and focusing on computer-aided diagnosis (CAD). Application areas include diagnostics and prognostics of breast, colon, prostate and lung cancer, among others. Our group is among the international front runners in the field, evidenced for instance by the highly successful CAMELYON and PANDA Grand Challenges which we organized and published in JAMA and Nature Medicine.

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.

Profile

You are a creative and ambitious researcher with an MSc degree in Computer Science, Data Science, Engineering, Technical Medicine, Biomedical Sciences or similar, with a clear interest in artificial intelligence and medical image analysis.

Good communication and organizational skills are essential. Experience with deep learning and programming, preferably in Python, is a plus and should be evident from the (online) courses you've followed, your publication, your GitHub account, etc.

Employment conditions

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:

• The salary depends on education. Scale 10 will be offered to MSc medical graduates; a gross monthly salary between €3.493 and € 5.504. Those holding degrees in other disciplines will be offered scale 10A: 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.
• 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.

Application procedure

Are you ready to think further for our patients and our care? We would like to receive your application before 29 August 2024. We will then contact you shortly.

Good to know

• This position requires a Certificate of Conduct (VOG).
• You can find more information about our application procedure and frequently asked questions on our website.
• Will you be our new colleague? Then you will be given the time and space to get to know your role, your workplace, and your colleagues. An induction day for all new colleagues is an integral part of your onboarding program. 

We are recruiting for this position ourselves. Unsolicited marketing is not appreciated, but do feel free to share the vacancy in your network!

Contact

Any questions? Or wondering what it is like to work at Radboudumc? Then call, send a message or email to Geert Litjens, Full Professor. Use the Apply button to submit your application.