PhD student AI & Image Analysis in Frontotemporal Dementia

Job description

Frontotemporal dementia (FTD) is a type of dementia that has a debilitating effect on patients and their caregivers. About 20% of patients have genetic FTD caused by known pathogenetic mutations. For the other patients, who have sporadic FTD, diagnosis is slow (~4 years) with frequent misdiagnosis due to clinical, genetic and molecular heterogeneity. Thus, there is an urgent need for biomarkers that improve diagnosis of sporadic FTD and its pathological subtypes. Artificial intelligence is expected to play a key role here, driven by its expanding role in the medical field, in particular radiology, in combination with the growth of clinical data and medical imaging made available for medical research. 

This project focuses on the diagnosis of FTD by validating a comprehensive set of liquid and imaging biomarkers and developing an AI-driven diagnostic tool. As a PhD candidate on this project, you will apply state-of-the-art machine-learning based methodology, particularly deep neural networks and disease progression modeling, to address key challenges in FTD diagnosis. These key challenges are:

• To distinguish sporadic FTD from (non-)neurodegenerative disorders that show significant clinical/symptomatic overlap.
• To robustly detect FTD pathological subtypes in sporadic FTD.
• Pre-symptomatic identification of FTD onset. 

Your project will be embedded in the PREDICTFTD consortium, recently funded in Horizon Europe's funding call "Tackling diseases and reducing disease burden". PREDICTFTD is an international consortium bringing together 11 dementia and FTD cohorts from 7 clinical centres in 5 countries across Europe, working on development and validation of novel liquid and AI-based biomarkers. In collaboration with other partners of the consortium, your role is to develop diagnostic and predictive algorithms, based on the machine-learning methodologies that support clinicians in diagnosing FTD. In addition, you will contribute to the collection, harmonization and quantification of the multicentre imaging data, including the local cohort FTD-RisC. The FTD-RisC (Frontotemporal Dementia Risk Cohort) is a unique longitudinal research study on genetic FTD that has been running since 2010. For this, you will closely collaborate with datamanager(s) and PhD students from the PREDICTFTD study and the Alzheimer Center of the Erasmus MC.

Work environment

The research will be conducted at the Biomedical Imaging Group Rotterdam (BIGR), which is part of the department of Radiology & Nuclear Medicine of the Erasmus MC in Rotterdam. The department has an international character with a good balance between internationally recognised, high-end research and an excellent social working environment. 

The research is performed in the context of the Alzheimer Center Erasmus MC, which is a collaboration between the departments of Neurology, Geriatrics, and Radiology & Nuclear Medicine to provide excellent patient care, facilitate education, and conduct scientific research. The scientific research of the Alzheimer Center focuses on unique forms of dementia, such as genetic dementia and young-onset dementia. 

The supervision for this project will be provided by dr. Esther Bron, assistant professor in neuroimage analysis and machine learning, dr. Harro Seelaar, assistant professor and neurologist, and dr. Meike Vernooij, professor of population imaging (promotor). You will collaborate with a team of experienced researchers with backgrounds in image analysis, machine learning, radiology, neurology and neuropsychology. 

Qualifications and skills

• You should be an independent and highly motivated researcher with an MSc or MEng degree in a technical domain with a strong affinity for clinical application (e.g. Clinical Technology, Technical Medicine or Biomedical Technology/Engineering).
• Experience with machine learning and programming is highly valued.
• You should be able to communicate and work with researchers from various fields. Excellent proficiency in English is required.

Before you apply please check our conditions for employment.

Terms of employment

• You will receive a temporary position for 4 years. The gross monthly salary is € 3.017,- in the 1st year and gradually increases to € 3.824,- in the 4th year (scale OIO).
• Excellent fringe benefits, such as a 13th month that is already paid out in November and a individual travel expense package.
• An International Office which aids you in preparing for you arrival and stay.
• Pension insurance with ABP. We take care of approximately 2/3 of the monthly contribution.
• Special benefits, such as a incompany physiotherapist and bicycle repairer. And there is also a gym where you can work on your fitness after work.

More information

For more information about this position, please contact dr. Esther Bron, assistant professor, via 010 704 4078.

No agencies please.