About the project

Breast cancer is the most common cancer in women globally. Rising incidence and improvements in cancer care have contributed to a growing number of breast cancer survivors. As these cancer survivors live longer, and with the majority of the patients being older than 50, they are at higher risk of developing other chronic diseases and conditions, including cardiovascular disease (CVD), neurovascular disease, weight gain, and osteoporosis.

Imaging is an integral part of breast cancer care and follow-up. A large majority of breast cancer patients undergo the acquisition of radiotherapy planning computed tomography (CT) scans. In addition to the requested information about tumor anatomy and location, these scans also contain information on risk factors for other diseases, including high fat and low muscle mass. In daily clinical practice, this potentially valuable but unrequested information is not systematically assessed or reported. However, systematic assessment and reporting of the presence of (risk factors of) chronic conditions on radiotherapy planning CT scans would allow timely identification and treatment of high-risk patients, improving their long-term outcomes and quality of life.

About the role

Using radiotherapy planning CT scans, the PhD candidate will develop trustworthy AI systems for automated detection and quantification of the indicators of body composition, such as muscle mass and adipose tissue that are intensively investigated in relation to prognosis in cancer patients. 

The PhD project is embedded in the qurAI group at the Department of Biomedical Engineering and Physics and the Department of Radiology.

The qurAI group is an interfaculty, multidisciplinary group between the Department of Biomedical Engineering and Physics of the Amsterdam University Medical Center (AUMC) and the Institute of Informatics of the University of Amsterdam. The qurAI group focuses on the development, validation and clinical integration of AI solutions for data analysis challenges in healthcare. The group aims at designing and enabling socially responsible AI innovations in healthcare.

The project is part of the Horizon Europe-funded ARTILLERY-consortium (Artificial Intelligence for early detection of non-communicable disease risk in people with breast cancer).

Your profile

• A Master’s degree (or equivalent) in Biomedical Engineering, Artificial Intelligence, Computer Science, or a related subject;
• Previously demonstrated interest in machine learning, deep learning and medical image analysis, in the form of coursework, projects and academic publications, and an affinity with medical topics;
• Good programming skills, particularly in Python and ML-related libraries;
• High motivation in pursuing academic research;
• Fluency in English, both written and spoken.
• Motivation to work in an interdisciplinary team of medical doctors and engineers

We offer

• Salary increase of 4% effective November 2023
• A flying start to your career in research work in a metropolis with a diverse and open culture, and a multicultural society.
• Working with motivated colleagues from all corners of the world.
• You will start with a contract for one year (12 months) in accordance with the CAO UMC 2022-2023, with the possibility of extension for another three years (36 months).
• PhD students (Onderzoeker in Opleiding) are placed in scale 21, with a fulltime gross salary. The starting salary is € 2.789,-  and increases to € 3.536,- in the fourth year. The position is for 4 years.
• In addition to a good basic salary, you will receive, among other things, 8.3% year-end bonus and 8% vacation allowance. Calculate your net salary here.
• Pension via BeFrank

If you are interested please apply via this link.