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+MANDATORY
+title: PhD Position: AI-Based Opportunistic Screening of Pancreatic Cancer Using CT Scans
+groups: radiology, etc (determines on which website the vacancy or student project appears)
+closed: false (change to true when vacanct is closed)
+type: student (currently the following types are supported: general, student, student-aihealth)
+picture: vacancies/ai-based-opportunistic-screening-of-pancreatic-cancer-using-ct-scans.jpg (Image is collected from website-content/content/images/. Upload a rectangular image here)
+template: vacancy-single
+people: Natália Alves, Megan Schuurmans.
+description: Pancreatic cancer remains the deadliest cancer globally, primarily due to its late diagnosis when curative treatments are no longer feasible. Survival rates are devastatingly low, often less than 5% at five years. This PhD project addresses this critical challenge by developing advanced artificial intelligence (AI) tools to detect pancreatic cancer earlier, significantly improving the chances of timely treatment and increasing survival rates. 
+The focus is on opportunistic screening, which leverages routine CT scans already performed for other medical reasons to identify early signs of pancreatic cancer without requiring additional invasive tests. The candidate will work with an extensive database of over 100,000 CT scans and data from the PANORAMA challenge, which has set the foundation for AI-driven pancreatic cancer detection. 
+The responsibilities will involve developing and validating AI models for early detection and designing real-world solutions tailored to clinical scenarios. Collaboration with clinicians and researchers will be a key aspect of ensuring that the solutions are impactful and clinically relevant. The ideal candidate will have a strong technical background, programming skills in Python, and a keen interest in deep learning, medical imaging, and healthcare.
+This project provides access to state-of-the-art computational resources and a world-class research team. It also offers opportunities to publish in high-impact journals and present findings at leading conferences. This PhD position is a unique chance to tackle a high-impact problem at the intersection of AI and healthcare. Join us in transforming pancreatic cancer detection and giving patients a fighting chance at improved outcomes.
+
+
+## Clinical Problem
+
+Pancreatic cancer is the deadliest cancer worldwide, claiming the lives of nearly all patients diagnosed in its later stages. Tragically, most patients receive their diagnosis only after the cancer has progressed too far for curative treatment. As a result, survival rates remain devastatingly low—often less than 5% at five years.
+
+But what if we could detect pancreatic cancer earlier, before symptoms appear? Earlier detection could lead to earlier intervention, more treatment options, and ultimately, improve survival time. This PhD project aspires to tackle this critical challenge, using cutting-edge artificial intelligence (AI) to transform the way pancreatic cancer is detected.
+
+## Solution
+
+This research project will develop advanced AI tools that analyze routine CT scans to identify the earliest signs of pancreatic cancer, even in patients who may not yet show symptoms. By using AI to screen CT scans that are already being taken for other medical reasons, this approach—known as opportunistic screening—has the potential to detect cancer earlier without requiring additional invasive tests.
+
+The candidate will work with an extensive database of over 100,000 CT scans, as well as data from the PANORAMA challenge—the first international grand challenge for pancreatic cancer detection using CT scans—which provided 2,238 cases for training and over 1,000 cases for tuning and testing. Leveraging these resources, you will explore novel AI solutions tailored for opportunistic screening scenarios, pushing the boundaries of AI's capabilities in medical imaging.
+
+## Tasks
+
+- Develop and validate AI models for early detection of pancreatic cancer using large-scale imaging datasets.
+- Develop and validate AI solutions tailored for opportunistic screening in real-world clinical settings.
+- Collaborate with radiologists, clinicians, and researchers to ensure the solutions are clinically relevant and impactful.
+
+## Requirements
+
+- Master’s degree in computer science, mathematics, biomedical engineering, technical medicine, artificial intelligence, physics, or a related field.
+- Strong technical background and programming skills, particularly in Python.
+- Experience or interest in deep learning, medical imaging, and medical image analysis.
+
+## Why Join Us?
+
+- Work with a world-class research team dedicated to improving outcomes for cancer patients.
+- Access to state-of-the-art computational resources and groundbreaking datasets.
+- Opportunities to publish in high-impact journals and present at leading conferences.
+
+## Practical Information
+
+- **Project duration**: 4 years (PhD position).
+- **Location**: Radboud University Medical Center, Nijmegen.
+
+### Application Process
+
+Interested candidates are invited to submit:
+
+1. **Cover Letter**: Explain your interest in the position and highlight relevant experience.
+2. **Curriculum Vitae (CV)**: Detail your academic background, research experience, and technical skills.
+3. **References**: Provide contact information for academic or professional references.
+
+For more information, contact (Natalia Alves)[[email protected]] or (Megan Schuurmans)[[email protected]].