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At Radboud University, we aim to make an impact through our work. We achieve this by conducting groundbreaking research, providing high-quality education, offering excellent support, and fostering collaborations within and outside the university. In doing so, we contribute indispensably to a healthy, free world with equal opportunities for all. To accomplish this, we need even more colleagues who, based on their expertise, are willing to search for answers. We advocate for an inclusive community and welcome employees with diverse backgrounds, cultures, and perspectives. Will you also contribute to making the world a little better? You have a part to play.
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Faculty of Social Sciences
At the Faculty of Social Sciences, humanity and society are our focus; we study how people behave, think and feel. Within this context, we look at themes such as human behaviour and the human psyche, education and upbringing, communication, society and culture. The faculty provides education to 6,000 students and employs 700 staff. Education is organised into six programme clusters: Psychology; Artificial Intelligence; Pedagogical Sciences and Educational Sciences; Communication Science; Sociology; and Cultural Anthropology and Developmental Sociology, and the Radboud Centre Social Sciences as an institute for post-master education have been merged into the Social Sciences Education Institute. Our research is carried out within three research institutes: the Donders Centre for Cognition, the Behavioural Science Institute, and Radboud Social Cultural Research.
Are you interested in designing and analysing algorithms based on completely novel computing principles? And in collaborating with physics researchers to finetune Markov Chain Monte Carlo algorithms using new materials currently only available in specialist labs? Or in working towards computation principles of the next decade? Then this PhD position may be of interest to you!
In this PhD position you will develop and analyse a new class of Markov chain Monte Carlo algorithms (such as Gibbs Sampling and Metropolis-Hastings) that make use of a novel technology that is currently only available in specialist labs. Using dedicated photonic manipulation, researchers can build covarying bits out of magnetic fields at the nanoscale that can be used at speeds that are orders of magnitude faster than current CMOS technology. In order to demonstrate the computational power of so-called synchronised stochasticity for approximate Bayesian inference, you will develop novel MCMC algorithms that make use of this feature for energy, time and space efficiency. In addition to algorithm development, implementation (using an emulator) and simulation, you will also work on analysing the theoretical properties of these algorithms using the mathematical framework of randomised complexity theory.
You will be part of both the Probabilistic Graphical Models group at the Donders Centre for Cognition and the interdisciplinary team of researchers and PhD candidates on this consortium project. In addition to research in this domain, you will contribute to academic teaching in the BSc and MSc programmes in AI, follow courses offered by the Donders Graduate school and the national IPA and SIKS research schools, and collaborate with inspiring colleagues in the international PGM research community.
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 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.
You will join the Probabilistic Graphical Models Group, led by Prof. Johan Kwisthout, who will be your supervisor. This group studies the foundations and applications of Probabilistic Graphical Models (PGMs). The group's research is centred around two research lines: ‘PGMs for decision support systems’ and ‘Foundations of stochastic computing’. The first line focuses on explainability, trustworthiness, maintainability, online or federated learning etc. in Bayesian networks and other PGM models, particularly with applications in clinical decision support systems. The second research line focuses on topics such as approximate Bayesian inference, parameterised complexity classes for stochastic computing, and realisation of probability distributions and computations on them in novel materials and computing architectures. This position contributes to the second research line and to a better understanding of the computational power of synchronisation for algorithm design.
You can apply no later than June 13, 2024 only via the button below. Address your letter of application to Prof. Johan Kwisthout.
The first interviews will take place in mid-June. An interview date will be set in consultation with you. You will preferably start your employment as soon as possible.
We can imagine you're curious about our application procedure. It describes what you can expect during the application procedure and how we handle your personal data and internal and external candidates. If you wish to apply for a non-scientific position with a non-EU nationality, please take notice of the following information.
Type of employment | Temporary position |
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Contract type | Full-time/Part-time |
First day of employment | zo spoedig mogelijk |
Salary | Promovendus |
Salary |
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Number of positions | 1 |
Full-time equivalent | 0,8-1,0 |
City | Nijmegen |
County | Gelderland |
Country | Netherlands |
Reference number | 2024/106 |
Contact |
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Published | 17.May.2024 |
Last application date | 13.Jun.2024 11:59 PM CEST |