Explorations of the structure of human cognition often take one of two approaches: a top down view that builds models based upon high level theoretical architectures and compares the performance of these models with observed human behavior, or a bottom up view that attempts to derive structures through the analysis of low level brain imaging signals. Though these methods are often pursued separately, some attempts have been made to combine the two approaches, analyzing signals from brain imaging data through the framework of high level architectural model structures. The Common Model of Cognition (CMC), a consensus model drawn from decades of work in functional cognitive architectures, has been found to provide a reasonable account of brain activity in a variety of tasks and at rest. The success of the CMC is encouraging evidence for the presence of a singular underlying framework that drives cognition, as well as giving strong indications of structural features likely present in the brain. However, the CMC is, by design, a very simple account of cognition, consisting of only five high level cognitive components (Perception, Action, Working Memory, Procedural Memory, and Long Term Memory), each of which likely contains multiple networks of lower level components that contribute to cognition.
The goal of this project is to extend the methods of previous research involving the Common Model, by increasing the complexity of the model's network framework to include components that represent more specific cognitive functions. Perception, for example, can take multiple forms, primarily auditory and visual, but the current configuration of the CMC treats all perceptual activity as the same. Comparing this original model framework with one that separates the visual and auditory perceptual signals and allows them to interact with the rest of the network individually could provide valuable insight into how perceptual inputs are processed, and how that information interacts with the rest of the components in the brain’s network model. The sparse nature of the original CMC model provides myriad opportunities to explore these kinds of distinctions in all five of the basic high level components, ultimately providing a more complete picture of the shape and structure of cognitive processes within the brain.
In this project we will:
The objective of the temporary position is the production of a number of research articles in peer-reviewed scientific journals and conference proceedings, which together will form the basis of a thesis leading to a PhD degree (Dr) at the the University of Groningen.
Qualifications
The successful candidate should have:
The project will consist of a combination of organizing and handling a large data set, performing basic analysis of brain imaging data, building and troubleshooting models of cognitive structure, and performing statistical analysis of the model outputs. Expertise in each of these areas is not a requirement, but some basic experience in similar areas and/or a motivated interest in one or more of the project components is helpful.
Organisation
Founded in 1614, the University of Groningen enjoys an international reputation as a dynamic and innovative institution of higher education offering high-quality teaching and research. Flexible study programmes and academic career opportunities in a wide variety of disciplines encourage the 36,000 students and researchers alike to develop their own individual talents. As one of the best research universities in Europe, the University of Groningen has joined forces with other top universities and networks worldwide to become a truly global centre of knowledge.
Within the Faculty of Science and Engineering. A 4-year PhD position is available at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence with the topic of structural underpinnings of human cognition. The candidate would become a member of the Cognitive Modeling Group of the Artificial Intelligence Department, and will work under the supervision of Dr Catherine Sibert and Prof Niels Taatgen.
Conditions of employment
We offer you, following the Collective Labour Agreement for Dutch Universities:
The successful candidate will first be offered a temporary position of one year with the option of renewal for another three years. Prolongation of the contract is contingent on sufficient progress in the first year to indicate that a successful completion of the PhD thesis within the next three years is to be expected. A PhD training programme is part of the agreement and the successful candidate will be enrolled in the Graduate School of Science and Engineering.
Application
Application should include:
You can submit your application until 31 May 11:59pm / before 1 June 2022 Dutch local time (CET) by means of the application form (click on "Apply" below on the advertisement on the university website).
Applications received before 1 June 2022 will be given full consideration; however, the position will remain open until it is filled.
The University of Groningen strives to be a university in which students and staff are respected and feel at home, regardless of differences in background, experiences, perspectives, and identities. We believe that working on our core values of inclusion and equality are a joint responsibility and we are constructively working on creating a socially safe environment. Diversity among students and staff members enriches academic debate and contributes to the quality of our teaching and research. We therefore invite applicants from underrepresented groups in particular to apply. For more information, see also our diversity policy webpage: https://www.rug.nl/(...)rsity-and-inclusion/
Our selection procedure follows the guidelines of the Recruitment code (NVP): https://www.nvp-hrnetwerk.nl/sollicitatiecode/ and European Commission's European Code of Conduct for recruitment of researchers: https://euraxess.ec.europa.eu/jobs/charter/code
Unsolicited marketing is not appreciated.
Information
For information you can contact:
Please do not use the e-mail address(es) above for applications.
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