Job opportunities at USI

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Università della Svizzera italiana
Faculty of Informatics

Learning Faces from DNA – PhD in novel deep learning methods for facial genetics applications

Within the context of an interdisciplinary project we plan to develop and investigate a novel methodology for reconstructing faces from DNA based on geometric deep learning. The research is supported by a 4-year co-funded FWO/SNF Belgian-Swiss research grant, as well as additional funding from ERC and Google. We are looking for a bright and motivated scientist with background in computer vision/geometry processing/computer graphics/machine learning and interest in statistical and imaging genetics who is willing to start a PhD at the University of Lugano, Switzerland and KU Leuven, Belgium under the joint supervision of Prof. Dr. Michael Bronstein, Dr. Peter Claes, and Prof. Dr. Dirk Vandermeulen.
The problem of recovering the geometric structure of the human face from DNA is an important instance of genotype-to-phenotype mapping, one of the Holy Grails of modern genetics. Successfully solving it leads to a breakthrough in many applications, ranging from personalized medicine to biometrics and forensics. For example, a better understanding of facial genetics will help in the delineation and diagnosis of clinical syndromes. Furthermore, in archaeology, ancient remains containing genetic material would allow us to reconstruct the faces of people who lived ages ago. Last but not least, the reconstruction of the face from DNA found at a crime scene could become a ground-breaking instrument that would allow to solve thousands of criminal investigations and cold cases.
However, the problem is complex involving the joint modeling of known and unknown associated genetic interactions with related facial features. To address this challenge, we are developing novel geometric deep learning methods ( that deal with geometric data and integrate prior biological knowledge. Therefore, in this project we aim to merge image and geometry processing with imaging genetics and computational biology.
Successful candidates will be enrolled in a co-supervised PhD between the University of Lugano and KU Leuven. The candidate will be primarily stationed in Switzerland and will have mid- and long-term visits at the KU Leuven, Faculty of Engineering, division ESAT-PSI ( and the Medical Image Research Center (MIRC) ( hosting one of the world’s leading labs in facial genetics. The research will be embedded in a very stimulating environment with state-of-the-art technical facilities and ample opportunities for interaction with various engineers, clinicians and experts on craniofacial genetics and geometric deep learning.
Ideal candidates should satisfy the following requirements:

  • Have or should soon obtain a Master's degree in engineering, computer science, artificial intelligence, or equivalent.
  • Strong mathematical background
  • Strong background in computer vision/graphics and machine learning with a publication record in top conferences (CVPR, ICCV, NIPS, ICML, ICLR, SIGGRAPH, SGP)
  • Preferably, background or interest in bioinformatics, computational biology, or statistical genetics.
  • Excellent programming skills, especially in python
  • Experience with programming in deep learning frameworks (TensorFlow, PyTorch, etc.)
  • Good skills in oral and written English.

For further information contact
Applications should include a short motivation letter, full CV (including a detailed transcript of university study results), and the names and contact information of at least two references.

Università della Svizzera italiana (USI)
Faculty of Informatics

The Faculty of Informatics provides an exciting environment in which to develop a research career. The successful student will gain a broad knowledge and understanding of the general field of informatics, as well as an in-depth specialization in an area of interest. Working with one or more members of the Faculty, the student will contribute original, useful, and scientifically valid ideas in their chosen area of research. In addition, the student will have an opportunity to participate in the educational mission of the Faculty. Current research interests of the Faculty include all aspects of software engineering, computer systems, information systems, algorithm design and verification.

Admission to the Ph.D. program is highly competitive. Applicants are admitted based on their research interests and experience, potential for success in the program, and compatibility with current needs of the Faculty. The official language of the Ph.D. program is English. In order to be admitted, the applicant must have completed a Masters degree in computer science, informatics, or a closely related field prior to joining the program.

Further information, including detailed application instructions, are available at