- Employment
- 0.7 - 1.0 FTE
- Gross monthly salary
- € 4,332 - € 5,929
- Required background
- PhD
- Organizational unit
- Faculty of Social Sciences
- Application deadline
- 01 October 2023
Apply now
Are you interested in Bayesian networks in foundational topics and their application in clinical decision support systems? Do you want to work in an interdisciplinary environment and collaborate with mathematicians, cognitive scientists and medical specialists? If so, this vacancy may be for you!
The Personalised Care in Oncology (PersOn) consortium is looking for a Postdoctoral Researcher in Probabilistic Graphical Models (PGM) to work on explainability and justification in Bayesian networks. Together with other postdoctoral researchers and PhD candidates from various backgrounds, you will lay the foundations for the next generation of clinical decision support systems for treatment and follow-up in oncology. You will work closely together with other PGM experts, as well as with researchers, healthcare practitioners, and stakeholders in explainable decision support. Your work will involve foundational research, advancing the state of the art in Bayesian networks, as well as applied research, focusing on user requirements in terms of explanation and justification to help advance shared decision making about personalised healthcare.
You will be embedded in the Foundations of Natural and Stochastic Computing group within the AI department, where fundamental and applied research on Bayesian networks is one of the core research lines. You will be expected to help define the group's research focus and positioning within the Donders Centre for Cognition (DCC) and in the international PGM community, and to help maintain a safe and inspiring research environment for our team members. If so desired, you will be given the opportunity to develop your teaching skills, helping you further qualify for a career as independent academic researcher.
Profile
- You have a PhD in computer science, artificial intelligence, applied mathematics, or a similar field.
- You have a strong background in AI research, with a focus on theoretical and/or applied work in probabilistic graphical models, as demonstrated by relevant conference or journal publications.
- You are motivated to work in a team, contribute to team science, and to the smooth functioning of the group and department, as well as pursue your independent research line.
- You are fluent in written and spoken English.
- Affinity with the healthcare domain is preferred.
We are
The Donders Institute for Brain, Cognition and Behaviour is 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 decision-making , 3. Development and lifelong plasticity , 4. Natural computing & 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.
The Donders Centre for Cognition, embedded in the Faculty of Social Sciences, is one of the four research centres of the Donders Institute, hosting the AI department, where you will be embedded in the Foundations of Natural and Stochastic Computing group , one of the PI groups within AI. The AI programme consists of a Bachelor's, Pre-master's, and Master's programme, and currently hosts about 750 students, 40% of whom are women. Within the Dutch AI landscape, research and education in Nijmegen has a strong cognitive focus, aimed at understanding natural cognition using AI tools, building brain-inspired AI systems, and improving the interaction between human and artificial intelligence. Focus areas are machine learning, adaptive systems, neurotechnology, brain-inspired computing, computational cognitive science, probabilistic graphical models, and the societal impact of AI. Important application areas are AI for healthcare, neurotechnology, brain-computer interfacing, and sustainable AI.
Radboud University
We want to get the best out of science, others and ourselves. Why? Because this is what the world around us desperately needs. Leading research and education make an indispensable contribution to a healthy, free world with equal opportunities for all. This is what unites the more than 24,000 students and 5,600 employees at Radboud University. And this requires even more talent, collaboration and lifelong learning. You have a part to play!
We offer
- It concerns an employment for 0.7 (48 months) - 1.0 (33,5 months) 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 2,8 - 4 year(s).
- 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 Dr Johan Kwisthout, PersOn programme leader, supervisor at +31 (0)24 3655977 or j.kwisthout@donders.ru.nl .
Practical information and applying
You can apply until 1 October 2023, exclusively using the button below. Kindly address your application to Dr Johan Kwisthout. Please fill in the application form and attach the following documents:
- A Letter of motivation.
- Your CV.
- A research plan (1-2 pages).
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.
Apply now Application deadline 01 October 2023
We would like to recruit our new colleague ourselves. Acquisition in response to this vacancy will not be appreciated.
Dr Kwisthout, J.H.P. (Johan)
PersOn programme leader, supervisor
j.kwisthout@donders.ru.nl +31 24 365 59 77
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When are you an internal candidate?
You are an internal candidate if you:
- Work at Radboud University (i.e. have an employment contract with Radboud University).
- Are a former Radboud University employee receiving unemployment (WW/BWNU) benefits paid by Radboud University (which started less than two years ago or resulted from the discontinuation of your job/redundancy).
- Currently work as a student employee at Radboud University through the campus employment office.
- Work as a temporary employee at, or have been seconded to, Radboud University.
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Last modified: 01 August 2023
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