PhD in fairness and responsible datasets for face recognition

The Idiap Research Institute and its Biometrics Security and Privacy group seeks qualified candidates for one PhD student position on the topic of fairness and responsible datasets for face recognition.

The research will be funded by the Hasher foundation under the Hasler Responsible AI program, and carried our jointly with the University of Zurich.

Face recognition (FR) is a biometric trait vastly used in practical applications but fairness aspects arise when decisions favor one demographic group over others [1]. Issues with unfair FR models have been constantly reported in the media (
FR research with large-scale datasets that respect people’s privacy is now a real concern that the research community must respond to [2].
In this research project, we will investigate strategies to close the fairness and ethics gap. First we will explore strategies to assess and close the fairness gap at training and scoring time through normalisation or regularisation. Second we will research mechanisms to generate synthetic datasets that are diverse and large-scale.

Applications can be submitted at any time but the position should be filled as soon as possible with a possible starting date early 2022 (to be negotiated).
In addition to the usual CV, we strongly encourage applicants to clearly identify in a cover letter how they could contribute to our activities.

The research will be carried out in the Biometric Security and Privacy group (Prof Sebastien Marcel) at Idiap. The research will rely on previous knowledge and software developed at Idiap, more specifically Bob toolkit. Reproducible research is a cornerstone of our activities. Hence a strong involvement in open source libraries such as Bob are expected.

Appointments as a PhD student are typically for 4 years, conditional to successful progress, and should lead to a PhD dissertation, granted by the "Université de Lausanne (UNIL)" or “Ecole Polytechnique Fédérale de Lausanne (EPFL)”. The annual gross salary in the first year is 52,400 Swiss Francs.

Working at Idiap in Martigny, the successful candidate will become a doctoral student at UNIL or EPFL, and thus also has to be accepted for enrolment by the Ecole des Sciences Criminelles (ESC) at UNIL or the Electrical Engineering Doctoral School (EDEE) at EPFL before joining Idiap.
The ideal candidate should hold a Master degree in computer science, engineering or related fields. The applicant should have a background in statistics, applied mathematics, optimization, linear algebra and signal processing. The applicant should also have strong programming skills and be familiar with Python, C/C++ (MATLAB is not a plus), various scripting languages and with the Linux environment. Knowledge in machine learning and more particularly deep learning (TensorFlow or pyTorch) is an asset. Shortlisted candidate may undergo a series of tests including technical reading and writing in English and programming (in Python and/or C/C++).


How to apply:  Interested candidates are invited to submit a cover letter, a detailed CV, and the names of three references through the Idiap online recruitment system:

PhD in fairness and responsible datasets for face recognition