PhD student ENSEMBLe project: European Newborn Study: Early Markers for a Better LifE.

You will join a team focused on improving the early diagnosis and personalized prognosis of cerebral palsy (CP) by collecting clinical data and developing a machine learning tool that integrates multiple diagnostic modalities.

What you will do

Cerebral palsy (CP) is the leading cause of physical disability in children but is often diagnosed too late, delaying intervention until after critical neuroplastic windows have passed. Recent guidelines have outlined reliable tools for early CP detection, combining brain MRI, EEG, and clinical assessments such as the General Movement Assessment (GMA) and the Hammersmith Infant Neurological Examination (HINE). However, current predictive models lack integration of these modalities and precision in individualized diagnosis and prognosis.

As part of the ENSEMBLE Project—a multinational study funded by the Fondation Paralysie Cérébrale—you will help develop a machine learning-based multimodal prediction tool for CP diagnosis and long-term outcomes. This tool will integrate advanced clinical assessments to provide personalized prognoses for motor, cognitive, and behavioral outcomes, enhancing family counseling and early intervention strategies.

Your responsibilities will include:

• Developing and validating a machine learning prediction model for CP and related outcomes using neonatal MRI, EEG, GMA, HINE, and clinical data.
• Coordinating patient inclusion, data collection, and analysis across multiple NICUs in five European countries.
• Harmonizing protocols across study centers and engaging with families to gather clinical and psychosocial data.

Where you will work

You will join the Department of Neonatology at the Wilhelmina Children’s Hospital (WKZ), an internationally recognized neonatal neurology expertise center. Collaborating with neonatologists, rehabilitation specialists, machine learning experts, and the Family Advisory Council (FAC), you will work at the intersection of clinical care and research. FAC will support co-creation of recommendations and strategies for implementing ML tools in neonatal care.

The department of Neonatology specializes in understanding and treating brain injuries in critically ill newborns, utilizing advanced brain imaging, bedside neuromonitoring, and standard long-term follow-up.

What you bring

We are looking for a motivated, team-oriented, and empathetic researcher with:

• A Master’s degree in Technical Medicine, Biomedical Engineering, Neuroscience & Cognition, or a related field.
• Demonstratable working experience in applying machine learning, preferably to clinical data.
• Excellent communication skills and the ability to engage with parents in high-stress situations.
• Proficiency in English and Dutch, both spoken and written.

We consider it an advantage if you bring the following:

• Experience in MRI brain imaging and/or EEG analysis

Interviews will take place on December 1st in the afternoon (2:00-4:00 PM) and possibly on December 5th in the morning (11:00 AM-12:30 PM).

What we offer

• Possibilities to develop yourself personally and professionally.
• The option to select additional employment benefits in exchange for gross salary, such as purchasing a bicycle and memberships.