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  • Twee stagiairs zorginnovatie die de ‘Innovatie potentie’ van GGZ Delfland weten te mobiliseren

    Help jij ons om onze cliënten -met innovaties- keuzes en regie te geven?

    GGZ Delfland
    Delft
  • Vacancy

    PhD position: Atherosclerotic Plaque Biomechanics / Carotid Plaque Imaging

    Department of Biomedical Engineering / Erasmus MC
    Rotterdam, Netherlands
  • Internship

    Simulating the effect of low gravity on microorganisms

    Perform experiments to test the effect of alternating gravity (clinostat) on bacterial growth.

    TU Delft (in collaboration with ESA and UNNOSA)
    Delft and Cologne, Netherlands and Germany
  • Internship

    Automatic algorithm selection for Radiomics

    The goal of this internship is to extend automatic algorithm selection to different image processing areas for Radiomics.

    Erasmus MC
    Rotterdam, Netherlands
  • Internship

    Semantic segmentation for Radiomics

    The goal of this internship is to find a deep learning segmentation approach to create robust medical image features.

    Erasmus MC
    Rotterdam, Netherlands
  • Internship

    Template space construction for voxelwise classification of Alzheimer’s disease

    In this project, you will develop improved image analysis methods for automated diagnosis of Alzheimer’s disease.

    Erasmus MC
    Rotterdam, Netherlands
  • Internship

    Longitudinal analysis of atrophy in Alzheimer’s disease

    In this project, you will develop a method to accurately assess atrophy in longitudinal data to study the progression of Alzheimer’s disease.

    Erasmus MC
    Rotterdam, Netherlands
  • Internship

    Progression of brain perfusion in aging and Alzheimer’s disease.

    In this project, you will work on the quantification of cerebral blood flow from ASL and apply the event-based model to study the processes of aging and disease.

    Erasmus MC
    Rotterdam, Netherlands
  • Vacancy

    PhD Data-Driven Design & Cardiology

    Research with impact @ TU Delft Industrial Design Engineering

    TU Delft Industrial Design Engineering - CardioLab
    Delft and Eindhoven, Netherlands
  • Internship

    Deep Learning for transforming ConeBeam CT images to CT images for Radiotherapy treatment planning

    Radiotherapy is conventionally planned on CT images. Imaging provided at the treatment site often is Cone Beam CT, which can not be directly used to create (or update) radiotherapy plans. Development of a method that automatically transforms such a Cone Beam CT to a normal CT may facilitate faster and more accurate treatment.

    Radiation Oncology / Biomedical Imaging Group Rotterdam, Erasmus MC
    Rotterdam