PhD AI-based analysis of fetal ultrasound

Medical imaging plays an essential role in disease detection, diagnosis, and aftercare. The accessibility to medical imaging is however challenged by the high costs of imaging devices, availability and required expertise of personnel to operate these devices and to analyze and interpret the resulting images. Our NWO-funded project, "AI4AI: Artificial Intelligence for Accessible Medical Imaging", aims to address these by developing artificial intelligence (AI) technologies to enable the use of more affordable devices, to allow operation by nonspecialized personnel, and to allow automated interpretation.

As a PhD student you will develop novel deep learning methods for identification of fetal growth abnormality from ultrasound. The cornerstone of prenatal care is monitoring of fetal growth primarily to detect fetal growth restriction, a major cause of perinatal morbidity and mortality. Growth-restricted fetuses benefit from delivery before the onset of fetal hypoxia and its ensuing adverse outcomes. Thus, timely identification of fetuses affected by growth restriction has the potential to reduce morbidity and mortality, especially in low- and middle-income countries. Obtaining accurate and complex measurement for reliable detection of fetal growth restriction requires a high level of expertise, limiting the analysis to specialized centers. Therefore, to allow high quality care, closer to patients’ home as well as in the areas where very specialized expertise is scarce, you will develop autonomous AI-based systems that support ultrasound acquisition and interpretation.

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 you will:

• Complete and defend a PhD thesis within the official appointment duration of four years;
• Publish and present your work in journals and international conferences;
• Be an active part of the qurAI group and its activities;
• Actively participate in the AI4AI consortium;
• Assist in educational activities and supervision of bachelor and master students.

• A flying start to your career in scientific research.
• Plenty of room for your drive to shape tomorrow's healthcare.
• Working on large-scale and in-house research, with motivated colleagues from all over the world.
• You will be employed by Amsterdam UMC Research BV.
• A contract for 12 months, with the intention to extend for a total of 4 years. The Guideline PhD contract applies to this vacancy.
• Salary scale OIO: € 3.017 to € 3.824 gross per month based on full-time employment (depending on education and experience) and a year-end bonus of 8.3%. Calculate your net salary here.
• Holiday hours: 190,4 per year for fulltime and a possibility to save additional hours.
• Pension accrual with BeFrank, a modern, comprehensible and fairly priced pension.
• For >7 km each way, 100% reimbursement for public transport travel costs and, for private transport, €0.18 per km up to a maximum of 40 km each way.
• Do you prefer walking or cycling? Take advantage of our good bike scheme. Moreover, you will receive a reimbursement of €0.18 per km.

Watch this video with more information about joining Amsterdam UMC Research BV.

Amsterdam UMC Research BV supports non-profit scientific research. In doing so, we provide researchers with everything they need to excel. Our principal investigators (PIs) and project leaders offer support in the field of project management, finance and human resources. In medical scientific research projects, legal support is also provided.

Watch the video to find out more.

Amsterdam UMC is one of the largest hospitals in the Netherlands and one of the prominent research institutes. The department of Biomedical Engineering & Physics participates in numerous international research projects and studies. This PhD project will be embedded in the qurAI group at the Department of Biomedical Engineering & Physics and Informatics Institute at the University of Amsterdam. Image analysis researchers at the Department of Biomedical Engineering & Physics and qurAI group have ample experience in the development and validation of AI image analysis methods. You will be embedded in the group of PhD students and postdocs developing AI methods for quantitative analysis of medical images and signals. Moreover, you will closely collaborate with gynecologists in Amsterdam UMC and other researchers in the consortium.