Reasearch Fellow RA1A in Face Recognition

Post–Doctoral Research Position in Face Recognition (Face modelling and matching)

Applications are invited from enthusiastic and talented individuals for a post–doctoral research position as part of an interdisciplinary research project. The position is available from 1 January 2016 through an EPSRC funded project in the area of automatic face recognition – FACER2VM. The work will be undertaken at the University of Surrey (UK) under the supervision of Professor Josef Kittler.

Project background

FACER2VM is a multidisciplinary collaborative research project funded by EPSRC. This project, led by the University of Surrey, involves Imperial College London and the University of Stirling, and is supported by the Home Office Centre for Applied Science and Technology, IBM, Digital Barriers, Cognitec, 3^rd Forensic, BBC and the European Association for Biometrics. The aim of the project is to develop solutions for unconstrained face recognition in which the engineering research will be informed by the psychology of human face matching. In particular, FACER2VM will focus on image degradations caused by lighting, resolution, occlusion and noise, as well as coping with natural modes of variations such as head pose and expression. The project offers an opportunity for successful candidates to work in an inspiring environment at the University’s Centre for Vision, Speech and Signal Processing, one of the UK’s premier research centres in image processing.

Our offer

As part of this project, we offer a full-time postdoctoral research position (RA1A) for two years. Although you will be based at the University of Surrey, you will be expected to travel occasionally to Imperial College London and University of Stirling for meetings and joint activities with our collaborators. In particular, your task will be to work on various aspects of unconstrained face recognition, and to integrate the algorithms developed into a face recognition system, as well as evaluating their effectiveness on data provided by the project partners.

Your profile

We are looking for a researcher with a PhD degree or currently enrolled on a PhD programme, with good skills and knowledge in face analysis and matching. Knowledge of 2D and 3D face modelling and model fitting, face image pre-processing and registration, is highly advantageous, as is experience in machine learning, statistical analysis and in handling large datasets. You need to have good programming and experimental skills and be confident working at the interface of image/video processing and machine learning. You should have experience of C/C++ and ideally GPU/CUDA implementation.

The candidates should be motivated and enthusiastic to work in a team environment and should have experience of communicating findings in journal papers. We are also looking for good written and spoken English language skills.

Your responsibilities

You will be expected to conduct research in Stream 1 of the FACER2VM project concerned with face modelling and face image matching, with a particular responsibility for the use of 3D face models in unconstrained face recognition. The duties will include reporting the results in top ranking pattern analysis and biometrics journals. You will actively contribute to FACER2VM project system integration activities and evaluation campaigns, as well as to outreach and technology transfer activities.

Information and application

For informal enquiries please contact Professor Josef Kittler (J.Kittler@surrey.ac.uk), tel. +44 (0)1483 689294.

Further details:

For more information and to apply online, please click on the ‘apply’ button below and download the further details.

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