You cannot apply for this job anymore.
Browse the current job offers or choose an item in the top navigation above.
The Department of Cognitive Science and Artificial Intelligence (CSAI) at Tilburg University, in collaboration with Tilburg School of Social and Behavioral Sciences (TSB) and the Elisabeth-Tweesteden Ziekenhuis (ETZ) is looking for a
Postdoctoral Researcher in Artificial Intelligence for a project on network analyses of cognitive tests for personalised diagnostics aimed at predicting Mild Cognitive Impairment and/or early Alzheimer’s disease.
The position in for a period of 2 years, between 0.8-1.0 fte (max. 38 hours per week) employment and starting from August 1st , 2021 (starting date flexible).
You contribute to research that is part of the WeCare program, focusing on AI contributions to personalized health care. In this project, we aim to develop personalized diagnostics of memory impairments, using adaptive online cognitive tests. Methods will draw on graph (neural) network analyses to uncover relationships between test items and demographic attributes, you will work towards generating flexible and personalized baselines/norms that will aid in creating sensitive and easy to use diagnostic tests, for use in primary care situations.
You perform scientific research at the intersection of AI and clinical neuropsychology:
Your professional environment
You will be part of the CSAI research group and collaborate closely with the Cognitive Neuropsychology department at TSB and the medical psychologists, geriatrists and neurologists at ETZ, through the WeCare programme. WeCare is the scientific collaboration programme of ETZ and TiU. WeCare aims to strengthen both parties in health (care) research to improve patient care. Our team consist of AI researchers, (neuro)psychologists and clinicians.
This project focuses on the application of AI techniques to generate individualized baselines for cognitive testing, using (among other memory tests) a Famous Faces Test which we are currently developing for use in an elderly population. We hope to use this test to detect early cognitive impairment and distinguish ‘normal’ cognitive aging from early signs of dementia. Alzheimer’s disease (AD) is the primary cause of dementia. Currently, over 270.000 people suffer from AD in the Netherlands alone and this number will double over the next decade (Alzheimer Stichting Fact Sheet, 2017). A string of failed clinical trials highlights the need to detect AD as early as possible rather than trying to treat after brain damage is irreversible (Scheltens et al., 2016; Sperling et al., 2014). Moreover, one pharmacological intervention (aducanumab) is currently awaiting final FDA approval (Sevigny et al., 2016), increasing the pressure on scientists and clinicians to work together to develop adequate and early diagnosis of patients who would benefit from such an intervention.
Early-stage symptoms of AD, such as memory decline, are often mistaken for normal aging, creating a barrier for patients to seek care. Furthermore, when individuals do seek help, usually through their GP, current standardized screening tests are often too general (e.g. the MOCA or MMSE which are screens for cognitive performance) and do not correct for individual characteristics, thereby losing sensitivity (Rentz et al., 2013; Nieuwenhuis-Mark, 2010). Consequently, patients are diagnosed much later than necessary or not at all. This is unfortunate (and costly), since the early detection of AD could significantly aid patients, carers and clinicians in organizing appropriate (future) care and increase the effectiveness of possible pharmacological and lifestyle interventions.
One of the hallmarks of AD is a steep decline in episodic memory, where recent memories are more affected that remote memories. The Famous Faces Test, a cognitive test in development by our team and a dedicated PhD student, is designed to be sensitive to this temporal gradient. In this project, we will use machine learning and network analysis tools to create a personalized model of memory performance based on demographics (e.g., age, gender, education) and health factors (e.g., physical activity, sleep), which have been shown to impact individual differences in cognitive abilities. These personalized predictions in turn allow the content of the memory tests to be tailored to the individual during the test (by adaptively presenting test items), to maximize its diagnostic sensitivity and thereby improve the early detection of potential cognitive decline in individual patients.
The central research questions are: Can predictions from machine learning models based on network analyses be used to generate personalized baseline for the early detection of dementia? Furthermore, is an online, adaptive test for detecting memory impairment as good as diagnoses generated in current clinical practice? If so, the online cognitive diagnostics platform could act as a low-cost longitudinal screening tool for the early detection of memory decline and follow up, to be deployed in primary care. This would be a proof-of-principle for such a successful precision medicine approach to the online detection of memory disorders, that could eventually be extended to other cognitive domains as well.
This postdoc position will be jointly supervised by dr. Marijn van Wingerden, AI-researcher (CSAI) and dr. Ruth Mark (TSB) and supported by a wider academic team including prof. Yvonne Brehmer (TSB). Collaborators include: prof. Eric Postma (CSAI) (AI) and dr. Gerwin Roks (Neurology, ETZ). Support in clinical translation will be provided by dr. Hetty Scholten (ETZ).
Fixed-term contract: 2 years.
The junior researcher will be employed at the CSAI department, Tilburg School of Digital Sciences and Humanities. We offer:
Research and education at the Tilburg School of Humanities and Digital Sciences (TSHD) has a unique focus on humans in the context of the globalizing digital society, on the development of artificial intelligence and interactive technologies, on their impact on communication, culture and society, and on moral and existential challenges that arise. The School of Humanities and Digital Sciences consists of four departments: Communication and Cognition, Cognitive Science and Artificial Intelligence, Culture Studies and Philosophy; several research institutes and a faculty office. Also the University College Tilburg is part of the School. Each year around 275 students commence a Bachelor or (Pre) Master Program. The School has approximately 2000 students and 250 employees.
We like to make it easy for you, sign in for these and other useful features: