PhD in Generating artificial EEG by combining AI and cognitive models (1.0 FTE)

Updated: about 1 month ago
Deadline: 17 Oct 2022

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.

This is an interdisciplinary PhD position belonging to the newly-founded Jantina Tammes school of the University of Groningen. The PhD is a collaboration between the Faculty of Science and Engineering and the University Medical Centre Groningen. The candidate will be embedded in the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence within the cognitive modeling group and will work under the joint supervision of Dr Marieke van Vugt, Prof. Natasha Maurits and Prof. Joukje van der Naalt.


Job description

We invite applications for a fully-funded four-year PhD position in the Jantina Tammes School of the University of Groningen, The Netherlands. This PhD position is a collaboration between the Cognitive Modeling group (Marieke van Vugt,

https://mkvanvugt.wordpress.com

) and the department of Neurology of the University Medical Center Groningen (Natasha Maurits,

https://www.clinicalneuroengineering.com

& Joukje van der Naalt,

https://www.rug.nl/staff/j.van.der.naalt/

).

When clinical or cognitive questions are addressed by using deep learning or machine learning on the basis of electroencephalography (EEG) data, the availability of limited EEG data presents a significant challenge. There are at least two types of limitations on data. Firstly, it may not be possible to find enough participants due to the rarity of the disease or challenging inclusion criteria. Secondly, it may be too time-consuming, too difficult or too exhausting, to obtain enough data for within-participant classification or prediction.

A solution that has been proposed to solve the limited data problem is Generative Adversarial Networks (GANs). GANs provide an unsupervised learning method that was applied to the generation of synthetic EEG data for the first time in 2018. However, GANs have some limitations. As the GAN can only sample from a limited dataset, i.e., the real data that it is presented with, it cannot take into account the possibilities of the entire space of potential real EEG data. This limitation is especially important when the real EEG dataset is small, or obtained from a nonrepresentative sample of the population.

To improve upon current methods, in this project knowledge about underlying cognitive processes will be taken into account in the generation of artificial EEG signals to be presented to the discriminator part of the GAN network. This cognitive component will be derived from the Adaptive Control of Thought—Rational (ACT-R) cognitive architecture. ACT-R is a cognitive architecture that has been used for decades to model and predict behavior on a wide range of cognitive tasks including attentional blink tasks, complex working memory tasks, associative memory tasks and more. Moreover, it has been linked to brain activity through EEG and fMRI.

The position is one of a large number of new PhD positions embedded in the new interdisciplinary schools of the University of Groningen. Consequently, the student will have ample opportunity to interact with other PhD students and staff who are interested in pursuing interdisciplinary research on the intersection between AI, psychology, neuroscience and medicine.


Qualifications

A successful candidate has a Master's degree in Artificial Intelligence, Cognitive Neuroscience, Mathematical Psychology, Neural Engineering or a related field, and solid programming skills. Experience in psychology, cognitive neuroscience, machine learning or EEG analysis is a plus. Good communication skills (both verbal and written) in English are a prerequisite. Knowledge of Dutch at the B1 level is a plus. The candidate should be enthusiastic about research, capable of learning new skills, and happy working both independently and in collaboration with other scientists.


Conditions of employment

We offer you, following the Collective Labour Agreement for Dutch Universities:

• a salary of € 2,541 gross per month in the first year, up to a maximum of € 3,247 gross per month in the fourth and final year for a full-time working week
• a holiday allowance of 8% gross annual income and an 8.3% year-end bonus
• a full-time position (1.0 FTE). 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.

Start date is flexible, 1 February 2022 at the earliest


Information

For information you can contact:

Marieke van Vugt,   m.k.van.vugt@rug.nl

Natasha Maurits,   n.m.maurits@umcg.nl

(please do not use the email addresses above for applications)


Additional information
Prof. Natasha Maurits
Prof. Joukje van der Naalt
Dr Marieke van Vugt
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