PhD in AI-based analysis of cardiovascular disease in breast cancer patients




We are seeking a highly motivated and talented PhD-candidate to develop deep learning methods for analysis of cardiovascular disease in breast cancer survivors

About vacancy

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.  For example, the amount of coronary artery calcifications indicates a risk of heart infarction. 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 might allow timely identification and treatment of high-risk patients, improving their long-term outcomes and quality of life.

About the role

As a PhD candidate you will develop trustworthy AI systems for automated detection and quantification of known and novel imaging biomarkers indicating the presence of cardiovascular disease in CT scans made for radiotherapy planning.

The PhD project is embedded in the interfaculty and multidisciplinary qurAI 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
  • Reimbursement of 75% of your public transport costs. Would you rather travel by bike? Then we have a good bicycle scheme.
  • An active staff association and the Young Amsterdam UMC association, both of which organize fun (sports) activities and events.

If you are interested, please apply here.