Application is currently ongoing for the PhD Positions in Deep learning medical imaging pancreas, Radboud UMC Netherlands 2021.
Pancreatic cancer (PDAC) will soon become the second leading cause of cancer-related death in Western societies, worldwide half a million deaths per year. PDAC has the lowest survival of all cancers (median survival time of 4.6 months, with patients losing 98% of their healthy life expectancy). The biggest challenge in the management of PDAC and new treatment development is the current inability of patient stratification.
Genomics technologies such as next-generation whole-genome sequencing (WGS) and liquid biopsy (ctDNA) are emerging, but not yet routinely used in PDAC diagnosis. Major R&D investments in prostate, lung, and breast cancer have resulted in stabilizing or decreasing mortality. No evidence-based personalized medicine approach for PDAC is currently available in the clinical practice.
Artificial Intelligence (AI) is transforming the field of healthcare. Worldwide interest in artificial intelligence (AI) is high and snowballing, fuelled by the availability of large datasets (“big data”). A new EU project (PANCAIM) aims to pool PDAC omics research data with medical imaging using AI to make an impact on PDAC patients and healthcare.
Duration: 4 years
Salary
min € 2495 – max € 3196 gross per month at full employment.
Job Requirements
- Radboud UMC seeks creative and enthusiastic researchers
- They must have an excellent MSc degree in a relevant field, such as medical image analysis, computer vision, or machine learning, or a medical degree with serious experience in programming and deep learning.
Applicants must have the ambition and academic skills to write and present scientific papers.
- They must have substantial experience with deep learning and good programming is essential and should be evident from the (online) courses they’ve followed, projects they’ve done, and their GitHub account.
- Experience in developing/exploring medical image analysis algorithms and a strong affinity with medical topics.
Application Process
Interested applicants should include the following in their application
- Curriculum Vitae,
- Motivation letter,
- List of grades, and links to publications,
- Master thesis or other works they have written in English.
To apply, click here
Application Deadline: December 31, 2020
For more information visit the official site.
