PhD image-based machine learning models in esophageal cancer

Esophageal cancer is a prevalent malignancy worldwide with a poor prognosis, with 572.000 new patients and 508.600 esophageal cancer related death worldwide per year. Chemoradiotherapy (carboplatin, paclitaxel, and concurrent 41.4 Gy radiotherapy) for esophageal cancer followed by surgery is currently regarded as a standard of care in clinical practice in the Netherlands. A significant proportion of patients have a pathological complete response(pCR) following neoadjuvant chemoradiotherapy(nCRT). However, pre-operative determination via endoscopies and imaging remains unreliable for patient selection. The objective of this study is to develop an image-based machine learning prediction model to assess pathologic response (treatment effect) to nCRT in esophageal cancer, by evaluating 18F-FDG PET/CT and DW-MRI / DCE-MRI scans prior, during and after nCRT, compared to the histopathological assessment of the resection specimen.

Would you like to know more about the different phases within the PhD trajectory? You can read more about this on this page.

As a PhD candidate within the AIFORCE project, you will contribute to groundbreaking research on response prediction in esophageal cancer patients using an image-based machine learning prediction model. Specifically, you will be involved in:

• Developing an image-based machine learning prediction model;
• Processing imaging data (18F-FDG PET/CT and DW-MRI / DCE-MRI scans);
• Validating the accuracy and reliability of the prediction model;
• Optimizing and validating the machine learning model, including validating model performance with clinical data and external datasets;
• Evaluating the clinical applicability of the model and determining its effectiveness in patient selection for surgery;
• Investigating how the model can be integrated into clinical practice.

We are looking for a dedicated researcher who works accurately and in a structured manner. You have strong communication and organizational skills and enjoy collaborating with different teams.

• You have a completed master’s degree in technical medicine, biomedical engineering, data science, artificial intelligence, or a related field, with an affinity for hospital environments;
• You have knowledge of medical terminology and handle confidential patient information with integrity;
• You have excellent proficiency in English, both in writing and presenting. Proficiency in Dutch is an advantage.