PhD/postdoc position: Utilizing Artificial Intelligence to Segment Echo Images of Tongue Cancer Intraoperatively to Facilitate Radical Resection

Description

Squamous cell carcinoma (SCC) of the tongue is a rare yet critical challenge in surgical oncology. Achieving a minimum resection margin of 5 mm is vital for patient outcomes but remains unmet in up to 85% of cases due to limited intraoperative feedback on tumor boundaries. Ultrasound (US) imaging has shown promise in distinguishing SCC from normal tissue, offering insights into tumor invasion depth and resection margins. However, its interpretation is subjective, heavily relying on clinician expertise.

This project funded by the Hanarth fund combines ultrasound imaging with histopathology data to train advanced AI models for automatic tumor segmentation, enabling surgeons to make informed decisions in real-time. By correlating detailed histopathological annotations with 3D reconstructions of US data, we aim to deliver precise, automated tumor delineation and improve the outcomes of SCC surgery.

Job Responsibilities

As a PhD candidate or postdoc, you'll focus on:

• Develop cutting-edge AI models: Train state-of-the-art deep learning models to segment SCC and healthy tissues using both US images and histopathology.
• Integrate multimodal data: Align histopathology slides with 3D ultrasound reconstructions.
• Refine imaging technology: Explore improvements in ultrasound physics, reconstruction algorithms, and data acquisition techniques to ensure high-quality inputs.
• Collaborate with clinicians: Work with medical specialists to validate the clinical utility of your algorithms and ensure their relevance in surgical settings.
• Collect data in the operating room: Participate in surgical theater data collection approximately once every two weeks to advance and expand the dataset needed to advance this research.

You'll be a part of the following groups:

• The AI for Oncology Group of Jonas Teuwen https://aiforoncology.nl
• The head and neck section of the surgical oncology department

About the AI for Oncology Lab

We are dedicated to developing AI solutions to enhance cancer diagnostics and treatments via methodological advancements and expert collaborations. We have a wide range of deep learning-based projects ranging from fundamental AI research to translational evaluation of existing algorithms. Check our website for more information.

Candidate Profile

We are seeking an ambitious, independent, and proactive researcher who is excited to work at the intersection of AI, imaging technology, and oncological surgery. Ideal candidates will have:

• A Master's degree in artificial intelligence, bioinformatics, computer science, physics, mathematics, or a similar field.
• Proficiency in deep learning and exceptional programming skills in python and preferably a compiled language such as Java or C++.
• Clear evidence of deep learning proficiency, reflected through coursework and GitHub repositories.
• Postdoctoral candidates must have extensive expertise in deep learning for medical image analysis.

We welcome applications that only partially qualify these requirements but make sure you argue why you are suitable for this position in your application letter. Please be aware that a master’s degree is required in the Netherlands to obtain a PhD degree.

Application Process

For inquiries or more about this position, reach out to Dr. Jonas Teuwen at j.teuwen@nki.nl, group leader AI for Oncology or Baris Karakullukcu at b.karakullukcu@nki.nl, head & neck surgeon. Submit your application letter, resume, and course list to Jonas Teuwen at j.teuwen@nki.nl with the subject line "APPLICATION: Hanarth AI position". Incomplete applications will be rejected without feedback. The position will remain open until filled, and applications are reviewed immediately upon arrival.