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PhD Training Program on 3D Facial Shape Analysis

The human face is complex three-dimensional structure that makes each of us uniquely distinguishable, but strongly determined by genetic factors. …

6 maanden geleden


's-Gravendijkwal, Rotterdam, Zuid-Holland
Tijdelijk contract / Tijdelijke opdracht
Uren per week:
36 - 36 uur
€ 2357 - € 3020 per maand


The human face is complex three-dimensional structure that makes each of us uniquely distinguishable, but strongly determined by genetic factors. Consequently, many developmental, psychiatric and genetic abnormalities have defined facial morphological features. However, the underlying complexity of facial morphology cannot be fully captured by simple geometric measures. Rather, it is now increasingly clear that the genetic determination of facial morphology and its relation with health outcomes requires more sophisticated quantitative approaches for capturing facial morphology. Recent advances in computational and methodological approaches have made possible accurate and precise derivation of facial traits.

This project will focus on developing methods (based on machine learning and deep learning technologies) to derive complex facial measurements in a unique dataset comprising thousands of 3D facial images of children from the prospective, longitudinal, population-based Generation R birth cohort and elderly population-based Rotterdam Study. 3D facial morphology exists in a high-dimensional feature space, which cannot be analyzed using simple Euclidean metrics. Accordingly, the ultimate aim of this project is to leverage the large-scale 3D facial imaging, which provides extensive genetic and epidemiological measures, to unravel the complexity between genetics, facial morphology and health outcomes.

The project leader is Prof.dr. Eppo Wolvius, Department of Oral & Maxillofacial Surgery, Special Dental Care, and Orthodontics. In collaboration with Prof.Dr. Wiro Niessen, Biomedical Imaging Group Rotterdam (BIGR); Dr. Fernando Rivadeneira, Department of Internal Medicine; Prof.Dr. Manfred Kayser, Department of Genetic Identification; Prof. Dr. Steven Kushner, Department of Psychiatry; Dr. Gennady Roshchupkin, Department of Medical Informatics, Department of Epidemiology; Dr. Stefan Boehringer, Biomedical Data Sciences, Leiden University Medical Center.


We are looking for enthusiastic candidates with a strong motivation to engage in the development and application of advanced analytical methods, including artificial intelligence, to tackle this important societal and healthcare challenge. Successful candidates are expected to have a strong quantitative or computer science background, excel at critical thinking, and highly motivated to solve clinical and epidemiological problems.

Furthermore the candidate should have an MSc degree in Mathematics, Computer Science, Statistics, Bioinformatics, Physics, Electrical Engineering, or in an equivalent discipline; strong knowledge of at least one scripting language: Python, R, Lua, Julia; experience with Linux operating system and Unix shell. Experience with machine learning and deep learning methods, experience in working with large datasets, knowledge or willingness to learn more about medical imaging, epidemiology and genetics are required. Just like good communication and writing skills in English and the ability to work, launch and embrace collaboration in a multidisciplinary setting.

Being able to present a certificate of good conduct, a valid proof of identity, diploma's and/ or relevant registration such as BIG/ RGS are conditions for the appointment.


You will receive a temporary position for 4 years. The gross monthly salary is € 2.357,- in the 1st year and increases to € 3.020,- in the 4th year (scale OIO). You will also receive a end of year bonus and a holiday gratification. The terms of employment are according to the Collective Bargaining Agreement for Dutch University Medical Centers (CAO UMC).

Additional information

For more information about this position and selection procedure please contact Gennady Roshchupkin, phone number: +31(0)10 704 40 78 or e-mail: g.roshchupkin@erasmusmc.nl. For queries regarding your application, please contact Jerry Chandansingh, Recruiter, by phone number: +31 (0)6 500 310 06.

If you are excited by the thought of this position and would like to apply, please do so by using the application form on our website.