Vacancy Researcher in Talent Track 'AI & Real-world data'

Job description

Radboudumc has a strong track record in developing AI-based diagnostic and prognostic models. We are expanding this strength substantially in our pursuit of patient-centred and innovative care, and we are also leveraging global developments in this area. The overall vision is to integrate multiple multimodal data sources from diverse studies and data collections – from clinical trials to routine care data – to better understand conditions and their course. The objective is to gain deeper insights into health, prevention and disease processes to support innovations in person-centred prevention and therapy. Real-world data studies and collections in combination with advanced models and AI solutions present specific challenges.

In the context of this position, the ambition is to unlock and leverage data that is already routinely collected, both within Radboudumc and with collaborative partners. The quality and validation of models usually require even more comprehensive datasets, such as international patient registries and international collaborations of the Radboudumc, which involve the sharing of large amounts of data, provide a solid foundation for AI and model development.

For these solutions to be successfully implemented in healthcare, it is essential that they are fit-for-purpose and permanently reliable, with the capacity to handle ever-increasing data and continuous learning models. This includes demonstrating quantifiable performance, such as added diagnostic value or accuracy of predictions at the individual patient level. It is of particular importance to Radboudumc as a hospital that the performance of applications can be demonstrated and secured, taking into account how they are used in practice by doctors and nurses. Given the learning nature of AI models, these are questions that require further research and methodology development.

Due to our focus on implementing AI to improve healthcare, we are seeking a postdoctoral researcher in the talent track to assistant professor or an assistant professor in the talent track to associate professor to spearhead the continuous evaluation and validation of advanced AI-based models based on real-world data on an international scale.

Our preferred candidate is interested in contributing to the development of data-driven care for patients inside and outside the hospital walls. The candidate is familiar with Radboudumc and its core values and is able to work in a person-oriented, innovative, networked manner, excelling as a team player in intended innovation projects.

Please upload a motivation letter, your curriculum vitae and the sectorplan application form that applies to your position. This form will guide you through some questions that are relevant for the selection

Place of work

In the focus area "data-driven health: AI, e-health and medical technology," we are committed to developing and implementing new technology in medical practice. The sector plan allows Radboudumc, together with regional, national and international collaboration partners, to continue building a self-learning healthcare system where data about our patients and treatment outcomes are used to improve the treatment of future patients and develop new prevention strategies. 



This position is partly funded by the resources made available by the medical sciences sector plan. With the sector plans, the Ministry of Education, Culture and Science (OCW) intends to make a structural contribution to the cohesion and cooperation between education and research, and to relieve stress and pressure related to science by offering more permanent contracts. In addition, the sector plans contribute to making joint and clear choices in the division of tasks and signatures of the Dutch universities.

Radboudumc fully supports these objectives and has seized this opportunity to strengthen and deepen a number of important existing strategic themes within Radboudumc. These are the themes of prevention, data-driven & Artificial Intelligence (AI), and molecular mechanisms of diseases and new treatments. These themes fit nicely on the thematic foci of the sector plan, namely prevention, data-driven innovation and the path from fundamental research to application. We hope this will not only give an impulse to the research within the radboudumc, but also strengthen the unique position of university medical centers: in no other place is the interaction between fundamental research and the treatment of (complex) patients so clearly present, and the potential for impact on both patients and healthy people so great.

Radboudumc
Welcome to Radboud university medical center (Radboudumc), where our research groups strive for innovative solutions that make impact on health and healthcare. We challenge the status quo to overcome current and future health challenges. Our goal is to shape the future of healthcare for generations to come. Our focus is on prevention, sustainability, and meaningful care, which we achieve through our in-depth understanding of disease mechanisms, clinical science, public health research, medical technology and data science. Our approach is centered on breakthroughs that can truly enhance personalized healthcare and public health. 

At Radboudumc, a comprehensive range of research programs provide the compass for our research efforts. Each program has a clear goal, where collaboration within and outside our organization is highly valued. We integrate care, education and research in partnership with our patients to ensure that our research programs have significant impact on health and healthcare. We invite you to join us in our mission to create a healthy future for all.

Profile

We are seeking a solution-oriented researcher with experience in quantitative modelling and analysis of complex (disease) processes, preferably using diverse data sources, and specifically medical and real-world data. You have a PhD degree with strong mathematical and statistical background, in medical biological context.

In addition you possess the profile below:

• You can demonstrate your experience in the development of complex quantitative models, preferably including machine learning and deep learning approaches.
• You have a cross-disciplinary outlook and enjoy working in interdisciplinary teams.
• You have proven interest in biomedical problems and drive to develop new methods and reliably put them into practice.
• You are persuasive collaborative and focused on structural solutions that have broad applicability.
• Experience in establishing educational training at Msc and post-graduate level is a plus.
• You are proactive and confident in the dynamic and complex environment of international medical scientific research.

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: 

• A gross monthly salary of between € 4.678 and € 6.402 (scale 11) or  € 5.677 and € 7.232 (scale 12) between for full-time employment (36 hours per week). You will also receive an 8% vacation allowance, an 8.3% end-of-year bonus, and, depending on the position, an allowance of 47% to 72% for working irregular hours.
• Plenty of opportunities to develop yourself. For example, you can follow various courses via our online learning environment. A lot of attention will also be paid to your wellbeing and vitality. For instance, you can take advantage of:
  • a 40% discount on gym membership at the Radboud Sports Center.
  • the Company Support Team and a personal coach if you experience a life-changing event.
  • a financially favorable option to work less through a generation scheme if you are approaching state retirement age.
  • support with achieving a good work-life balance at every stage of your life. This includes advice and training (from ‘Millennial Dilemmas’ to ‘Your Career After 57’), activities at our own mindfulness center, and informal caregiving consultations if you have any questions about combining your work and caregiving tasks at home.
• 168 vacation hours per year based on a 36-hour working week. Want more vacation? You can buy additional vacation hours with your end-of-year bonus.
• 26 weeks of parental leave, of which 9 weeks are paid.
• Extra-favorable leave conditions. For example, our short-term caregiving leave is not 2 but 4 weeks per year and even 12 weeks per year for partner and child.
• Pension accrual with the ABP Pension Fund. Radboud university medical center pays 70% of the pension contribution.
• Discount on the supplementary packages of two collective health insurance policies and on ten other types of insurance, from home insurance to legal assistance.
• A travel allowance via our Employment Conditions Selection Model and 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 26 July 2024. We will then contact you shortly. Please upload a motivation letter, your curriculum vitae and the sectorplan application form that applies to your position, see in the job description.

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 prof. dr. Peter-Bram 't Hoen, full professor. Use the Apply button to submit your application.