PhD Candidate in Artificial Intelligence: LUMC is seeking a proactive and analytical PhD candidate in Artificial Intelligence for Bone Tumors to develop and evaluate multimodal deep learning models that enhance diagnostics in the field of oncology. This opportunity combines cutting-edge AI research with clinical application, aiming to bridge the gap between advanced computational modeling and real-world medical practice.
Designation
PhD Candidate
Research Area
Artificial Intelligence, Medical Imaging, and Pathology
Location
Leiden University Medical Center (LUMC), Leiden, Netherlands
Eligibility/Qualification
- Master’s degree in Computer Science, Artificial Intelligence, Biomedical Engineering, or a related field with excellent academic results.
- Hands-on experience with Python and modern deep learning frameworks (e.g., PyTorch or TensorFlow).
- Familiarity with self-supervised learning and multiple instance learning, or a strong willingness to learn these skills.
- Knowledge of containerization technologies (Docker, Kubernetes), distributed computing, and version control (Git) is a plus.
- Strong communication skills and the ability to collaborate with researchers, clinicians, and IT professionals.
Job Description
As a PhD candidate, you will:
- Develop the multimodal BONE-CLASSifier by formulating and testing multiple instance learning algorithms and exploring innovative deep learning architectures.
- Design and conduct hypothesis-driven experiments, define evaluation metrics, and interpret model behaviors.
- Collaborate closely with clinicians, radiologists, and pathologists for integrating AI models into clinical workflows.
- Publish high-impact scientific papers, present findings at international conferences, and contribute to grant proposals.
How to Apply
Interested applicants should submit their application through the LUMC website. Ensure to include a detailed CV, cover letter, and any relevant documentation evidencing qualifications and experience.
Last Date to Apply
Open now
For more information, visit LUMC’s official webpage or contact relevant department representatives.
