PhD in Epidemiology on value-of-information from validating clinical prediction models and AI

Welcome to Maastricht University! 
Join Maastricht University as a PhD student in Epidemiology, advancing interdisciplinary methods to ensure reliable AI in healthcare through innovative statistical and health-economic approaches. You will develop value-of-information measures and software that help determine when an AI model is ready for use and when more research is needed.

PhD in Epidemiology on value-of-information from validating clinical prediction models and AI

• Our goal: Develop value-of-information methods to assess and improve the reliability of clinical prediction models and AI.
• Your colleagues: A VIDI project team with 2 PhD students and 1 postdoctoral researcher, supervised by Dr. Laure Wynants, working with clinicians, statisticians, epidemiologists, health economists and data scientists.

Clinical prediction models and Artificial intelligence (AI) can support diagnosis and prognosis, and support optimization of patient care. Whether this is achievable depends on the reliability of an AI-model. Testing of AI is often done on small numbers, and AI-models are not equally useful in all locations and patient populations. Reliability can be measured with value-of-information measures that reflect the risks of uncertainty, expressed as the expected number of misdiagnoses. This allows physicians and policymakers to decide for each AI-model: is it ready for use, or is more research needed?

In this project, you will develop and refine these value-of-information measures. In this role, you will conduct interdisciplinary research at the intersection of statistics and health economics to assess and enhance the reliability of AI models in healthcare. To support the dissemination of your methods, you will contribute to user-friendly statistical software, such as an R package, and develop guidance material for other researchers. You will share your findings through academic publications, conference presentations, and engagements with stakeholders. Additionally, you will actively contribute to the institute's academic environment by participating in seminars, workshops, and collaborative research.

What you do
Your daily worksite is the Department of Epidemiology at Maastricht University. Your day-to-day tasks and responsibilities are to:

• Develop new predictive performance and value-of-information metrics.
• Propose computational algorithms to estimate these metrics.
• Design and execute simulation studies to evaluate the above.
• Develop and test statistical software.
• Write user-friendly guidance on how to apply novel methodology.
• Deepen subject-matter knowledge through literature review and active engagement with current research developments.
• Work closely with academic advisors and collaborators to ensure research quality.
• Write up, publish and present findings, and assist with teaching duties.

Are you ready to set the course for the years ahead? Then we’d love to meet you. 

What you bring
We’re not looking for checkboxes; we’re interested in who you are and what you bring. Do you recognize yourself in this?
   

• Strong analytical and interdisciplinary mindset – You enjoy bridging medical statistics and health economics, and thrive in a dynamic research environment.
• Academic foundation – You have a Master’s degree in Statistics, Health-Economics, or equivalent.
• Relevant methods experience – You have knowledge of and/or experience with validation of prediction models (regression or supervised machine learning), health technology assessment, decision curve analysis, and/or value-of-information analysis.
• Programming skills – You can program in R, or you are proficient in another language and willing to learn R.
• Clear scientific communication – You master scientific English for speaking, reading, and writing. Knowledge of clinical epidemiology and/or Dutch is an asset.

What we offer
At Maastricht University, you’ll work in an international, open, and engaged environment. We offer: 

• An employment contract for a period of 12 months with a scope of 1 FTE. Upon a positive evaluation, an extension of 3 years will follow.
• Good employment conditions. A salary based on experience ranging from € 3059,-  to € 3881,-  gross per month (based on a full-time employment of 38 hours per week). In addition to the monthly salary, an 8.0% holiday allowance and an 8.3% year-end bonus are applicable.
• If you work full-time, you will be entitled to 29 vacation days and 4 additional public holidays per year, namely Carnival Monday, Carnival Tuesday, Good Friday, and Liberation Day. If you choose to accumulate compensation hours, an additional 12 days will be added.
• At Maastricht University, the well-being of our employees is of utmost importance. We offer flexible working hours and (after the first year) the possibility to work partly from home. You will receive a monthly commuting and internet allowance for this.
• Last but certainly not least, we provide the space and facilities for your personal and professional development. We facilitate this by offering a wide range of training programs and supporting well-established initiatives such as 'acknowledge and appreciate'.
• A close-knit community of colleagues to collaborate and grow with. 
• A solid pension plan via ABP, company fitness schemes, and access to various university sports facilities. 
• An inspiring work environment in the heart of Europe. 

About the Faculty of Health, Medicine and Life Sciences (FHML) and the Department of Epidemiology
FHML is committed to health in the broadest sense: from molecule to human, and from healthcare to prevention. We train healthcare professionals and researchers through innovative educational programmes and conduct groundbreaking research in health and well-being. Within FHML, the Department of Epidemiology aims to improve human health and well-being through user-relevant, multidisciplinary epidemiologic research and teaching, developing and validating tools and strategies for prevention, diagnosis, treatment and care.

Interested?
Are you interested in this exciting position but still have questions? Feel free to contact Dr. Laure Wynants at laure.wynants@maastrichtuniversity.nl for more information.

Apply now, no later than 21 April for this position.

Please upload your CV, motivation letter, grade list, contact information of 2 referees, research plan and publication list.

Apply now via the button below. We look forward to getting to know you!

About Maastricht University

At Maastricht University, we collaboratively seek solutions to help move the world forward. We do this with 23,300 students and 5,400 employees across 5 regional locations, 6 faculties, and more than 70 research institutes. We encourage you to push boundaries and discover new opportunities for yourself and the world around you. Together, we can find the answers for tomorrow. 

The vacancy is open for internal and external candidates. In case of equal qualifications, internal candidates will be prioritized.

At Maastricht University, we prefer to contact potential candidates directly. We therefore kindly ask that no agencies or intermediaries submit offers or approaches.

Maastricht University is committed to promoting and nurturing a diverse and inclusive community. We believe that diversity in our staff and student population contributes to the quality of research and education at UM, and strive to enable this through inclusive policies and innovative projects led by teams of staff and students. We encourage you to apply for this position.