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Els Ortibus

Top university

3 months ago

Multimodal markers of altered brain maturation and motor development in high-risk infants KU Leuven in Belgium

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Expired

Country flag

Country

Belgium

University

KU Leuven

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Keywords

Computer Science
Machine Learning
Biomedical Engineering
Signal Processing
Electrical Engineering
Medical Imaging
Artificial Intelligence
Eeg
Neuropsychology
Medical Science
Magnetic Resonance Imaging
Neurodevelopment
Preterm Birth
Statistics

About this position

PhD position at KU Leuven in multimodal markers of altered brain maturation and motor development in high-risk infants.

This interdisciplinary doctoral project is hosted by the Department of Development and Regeneration within the PRONTO research lab, in close collaboration with UZ Leuven, the Neonatology Unit of University Hospitals Leuven, the Department of Electrical Engineering, and the Centre for Developmental Disabilities. The project brings together expertise in neonatology, pediatric neurology, ophthalmology, rehabilitation sciences, engineering, and medical data analysis.

The research focuses on preterm infants at high risk for neurodevelopmental disorders, aiming to uncover how early brain maturation relates to later visuomotor and motor development. Using longitudinal data from the first two years of life, the project combines MRI, EEG, and wearable sensing to identify multimodal biomarkers of altered brain maturation and deficient bimanual coordination outcomes. The role involves supporting data acquisition, optimising processing pipelines, curating and integrating multimodal datasets, and developing advanced analyses including signal processing, machine learning, and AI-based modelling.

The position offers a fully funded, full-time PhD appointment for 4 years (initial 1-year contract, renewable up to 4 years), with salary according to KU Leuven standards and access to advanced infrastructure, interdisciplinary supervision, and doctoral training. The start date is 15 October 2026 or as soon as possible thereafter.

Applicants should have a master’s degree in a relevant field such as Biomedical Engineering, Applied Engineering, Biomechanics, Physics, Data Science, Neuroscience, or Biomedical Sciences. Strong academic performance is expected. Programming skills in Python, MATLAB and/or R are required, while experience with MRI, EEG, and wearable-sensor analysis is an advantage. English proficiency is mandatory, and willingness to learn Dutch is required. Candidates must also be willing to apply for a PhD fellowship in 2027 with institutional support.

Interested candidates should submit a motivation letter, CV, diploma copy if available, and contact information for two references. Informal enquiries can be directed to Prof. dr. Els Ortibus at [email protected]. Interviews are planned for the first two weeks of September 2026.

Funding details

Available

What's required

Applicants must hold a Master’s degree in Biomedical Engineering, Applied Engineering, Biomechanics, Physics, Data Science, Neuroscience, Biomedical Sciences, or a related field. Good to strong academic performance is required, with minimal distinction in the Master’s programme. Candidates should have a genuine interest in neurodevelopment, brain imaging, and signal processing, and strong motivation to conduct clinical research and engage with research participants. Proficiency in programming, including Python, MATLAB and/or R, is required. Experience with neuroimaging (MRI/EEG) and signal processing (including wearable sensors) is valuable but not mandatory. Strong analytical and problem-solving skills, the ability to work independently and collaboratively in a multidisciplinary team, and mastery of spoken and written English are mandatory. Willingness to acquire Dutch is required, and applicants must be willing to apply for a PhD fellowship in 2027 with support from the host institutions.

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Professors

Prof. dr. at KU Leuven

University Name
Country flag

United Kingdom

Research Interests

Statistics

Artificial Intelligence

Biomedical Engineering

Eeg

Electrical Engineering