9 May 2023
- Research Field
- Researcher Profile
Leading Researcher (R4)
Established Researcher (R3)
- Application Deadline
4 Jun 2023 - 22:00 (UTC)
- Type of Contract
- Job Status
- Hours Per Week
- Is the job funded through the EU Research Framework Programme?
Not funded by an EU programme
- Is the Job related to staff position within a Research Infrastructure?
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!
As Assistant Professor of Probabilistic Graphical Modelling (PGM) you will strengthen our research and education, particularly with healthcare as the application domain. You will be expected to contribute to the undergraduate and graduate programmes in Artificial Intelligence. More in particular, you will coordinate the AI for Healthcare course as well as develop a more specialist course in PGM. In addition, you will participate in the Healthy Data programme and contribute to its educational work package. You will supervise students and PhD candidates and/or mentor postdoctoral researchers within the AI department.
Your research should fit within the scope of the PGM research domain, including for example mathematical foundations, approximate inference, explainable and justifiable AI, structure and parameter learning, federated learning, sensitivity analysis, Gaussian processes, causal discovery, statistical methods, or non-parametric Bayes. Ideally you combine both theoretical work with practical applications such as clinical decision support systems.
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.
- You should have a PhD in computer science, artificial intelligence, applied mathematics, or a similar field, preferably with several years of postdoctoral experience.
- You have affinity with teaching, along with demonstrable teaching skills and the ability to deliver inspiring lectures, as evidenced by positive teaching assessments.
- You have obtained the University Teaching Qualification (UTQ) or are willing to acquire this qualification in the near future.
- 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 assist the smooth functioning of the group and department, as well as pursue your own independent research line.
- You are fluent in written and spoken English.
- Affinity with the healthcare domain is preferred.
- It concerns an employment for 0.8 - 1.0 FTE.
- The gross monthly salary amounts to a minimum of €3,974 and a maximum of €5,439 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 1 jaar met uitzicht op een vast dienstverband.
- 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.
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.
You can apply until 4 June 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).
- A teaching statement (1-2 pages).
The first round of interviews will take place on Monday 12 June. You would preferably begin employment on 1 September 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.
For questions about the position, please contact Dr Johan Kwisthout, Programme Director at +31 (0)24 365 59 77 or firstname.lastname@example.org .
- Website for additional job details
- Number of offers available
- Radboud University
- Postal Code
- 6525 XZ
- Houtlaan 4
Where to apply
- Postal Code
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