Employment0.8 - 1.0 FTE
Gross monthly salary€ 4,332 - € 5,929
Required backgroundPhD
Organizational unitFaculty of Social Sciences
Application deadline15 August 2023
We are seeking a highly motivated and skilled Postdoctoral Researcher to join our group at the AI department of the Donders institute and work on the prediction and control of complex stochastic processes.
You will contribute to the development of a theoretically sound and computationally scalable framework for understanding and predicting the evolution of longitudinal data (i.e. nowcasting, prognosis, anomaly detection) in the health domain. This is an exciting opportunity to contribute to cutting-edge research within the Healthy Data programme, focused on advancing AI techniques and their application to improve health and healthcare in society.
As a postdoctoral researcher, you will take on a key role in coordinating the project and collaborating closely with the research team, PhD candidates and staff members. Your responsibilities will include co-supervising PhD candidates, providing guidance and support in their research activities. You will work in collaboration with an ICT developer to adapt and optimise methods for health data applications. Your primary focus will be on developing and implementing techniques for the prediction and control of complex stochastic processes, with an emphasis on nowcasting, prognosis, anomaly detection, and understanding the impact of control policies. In addition, you will test and validate these methods using publicly available datasets and collaborate with partners in the Healthy Data programme to apply these methods to health data collected within the programme. Your research efforts will also involve the exploration and development of other techniques, such as distributed control, fractional-order control, and regression discontinuity methods. Overall, your work will contribute to the advancement of prediction and control methodologies and their application in the health domain, with a goal of making a significant impact in the field.
Profile
- You hold a PhD degree in a relevant field, such as artificial intelligence, computer science, applied mathematics, or a related discipline.
- You have a strong background in machine learning, dynamical systems, statistical modelling, and algorithms for analysing complex stochastic processes.
- You have experience working with longitudinal data, preferably in the health domain, and an understanding of the challenges associated with controlled dynamical systems perturbed by noise.
- You have proficiency in programming languages such as Python and experience with relevant libraries and frameworks (e.g. JAX, PyTorch).
- You have an excellent track record in scientific research as evidenced by publications in top-tier conferences and journals.
- You have excellent communication skills and an ability to collaborate effectively in a multidisciplinary team.
- You have demonstrated experience or an affinity with working in a scrum team.
We are
The Radboud Healthy Data Programme is a joint, digital transformation programme of Radboud University and the Radboud university medical center. Radboud Healthy Data aims to connect and further develop our expertise in health-related data management and
AI, with the purpose of enhancing the development of a responsible and sustainable digital infrastructure for the entire Radboud University campus. Focus areas in our programme are FAIR data stewardship, AI methods, education, ethical/legal/societal considerations, data-related community activities, and scientific breakthroughs. We build upon our strong history and ongoing activities with partners in our networks. Through Healthy Data, we will strengthen our data-driven infrastructure and our collaborative AI research at the Radboud University campus to improve health and healthcare in society.
Ideally, you therefore have experience or an affinity with working in a scrum team and know how to co-create sustainable solutions that will strengthen our data-driven infrastructure and/or AI applications for healthcare.
The
Donders Institute for Brain, Cognition and Behaviouris a world-class interfaculty research centre that houses more than 700 researchers devoted to understanding the mechanistic underpinnings of the human mind. Research at the Donders Institute is focused around four themes: 1. Language and communication, 2. Perception, action and control, 3. Plasticity and memory, 4. Neural computation and neurotechnology. Excellent, state-of-the-art research facilities are available for the broad range of neuroscience research that is being conducted at the Donders Institute. The Donders Institute has been assessed by an international evaluation committee as 'excellent' and recognised as a 'very stimulating environment for top researchers, as well as for young talent'. The Donders Institute fosters a collaborative, multidisciplinary, supportive research environment with a diverse international staff. English is the lingua franca at the Institute.
Radboud University
We are keen to meet critical thinkers who want to look closer at what really matters. People who, from their expertise, wish to contribute to a healthy, free world with equal opportunities for all. This ambition unites more than 24,000 students and 5,600 employees at Radboud University and requires even more talent, collaboration and lifelong learning. You have a part to play!
We offer
- It concerns an employment for 0.8 - 1.0 FTE.
- The gross monthly salary amounts to a minimum of €4,332 and a maximum of €5,929 based on a 38-hour working week, depending on previous education and number of years of relevant work experience (salary scale 11).
- You will receive 8% holiday allowance and 8.3% end-of-year bonus.
- It concerns a temporary employment for 4 years.
- You will be able to use our Dual Career and Family Care Services. Our Dual Career and Family Care Officer can assist you with family-related support, help your partner or spouse prepare for the local labour market, provide customized support in their search for employment and help your family settle in Nijmegen.
- Working for us means getting extra days off. In case of full-time employment, you can choose between 30 or 41 days of annual leave instead of the legally allotted 20.
Additional employment conditions
Work and science require good employment practices. This is reflected in Radboud University's primary and secondary
employment conditions. You can make arrangements for the best possible work-life balance with flexible working hours, various leave arrangements and working from home. You are also able to compose part of your employment conditions yourself, for example, exchange income for extra leave days and receive a reimbursement for your sports subscription. And of course, we offer a good pension plan. You are given plenty of room and responsibility to develop your talents and realise your ambitions. Therefore, we provide various training and development schemes.
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Would you like more information?
For questions about the position, please contact Marcel van Gerven, Project Lead, at marcel.vangerven [at] donders.ru.nl (marceldotvangervenatdondersdotrudotnl).
Practical information and applying
You can apply until 15 August 2023, exclusively using the button below. Kindly address your application to Marcel Van Gerven . Please fill in the application form and attach the following documents:
- A Letter of motivation.
- Your CV.
- Two recent publications.
- The contact details of two references who may be contacted for further information.
The first round of interview will take place on Friday 25 August. The second round of interviews will take place on Friday 1 September. You would preferably begin employment on 1 October 2023.
We can imagine you're curious about our
application procedure. It offers a rough outline of what you can expect during the application process, how we handle your personal data and how we deal with internal and external candidates.
Application deadline 15 August 2023
We would like to recruit our new colleague ourselves. Acquisition in response to this vacancy will not be appreciated.
Project Lead
marcel.vangerven [at] donders.ru.nl