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Anniversary Lectureship in Biometrics and Human Identification

Lancaster University - School of Computing and Communications

Interview Date: TBC

To support the advanced ERC-funded project H-unique, Lancaster University will appoint a new Anniversary Lecturer (equivalent to Assistant Professor) to take an active lead with Prof. Dame Sue Black and the research team to secure the goals of the research.

H-unique is a five year, €2.5M programme of research and will be the first multimodal automated interrogation of visible hand anatomy, through analysis and interpretation of human variation via images. It will be an interdisciplinary project, supported by anatomists, anthropologists, geneticists, bioinformaticians, image analysts and computer scientists. We will investigate inherent and acquired variation in search of uniqueness, as the hand retains and displays a multiplicity of anatomical variants formed by different aetiologies (genetics, development, environment, accident etc.).

Hard biometrics, such as fingerprints, are well understood and some soft biometrics are gaining traction within both biometric and forensic domains (e.g. superficial vein pattern, skin crease pattern, morphometry, scars, tattoos and pigmentation pattern). A combinatorial approach of soft and hard biometrics has not been previously attempted from images of the hand. We will pioneer the development of new methods that will release the full extent of variation locked within the visible anatomy of the human hand and reconstruct its discriminatory profile as a retro-engineered multimodal biometric. A significant step change is required in the science to both reliably and repeatably extract and compare anatomical information from large numbers of images especially when the hand is not in a standard position or when either the resolution or lighting in the image is not ideal. Large datasets are vital for this work to be legally admissible. Through citizen engagement with science, this research will collect images from over 5,000 participants, creating an active, open source, ground-truth dataset. It will examine and address the effects of variable image conditions on data extraction and will design algorithms that permit auto-pattern searching across large numbers of stored images of variable quality. This will provide a major novel breakthrough in the study of anatomical variation, with wide ranging, interdisciplinary and transdisciplinary impact.

You will typically have a background in Computer Science, Statistics, Machine Learning or a related discipline. Areas of interest include but are not limited to: algorithm & data structuring, image processing and biometric analysis.

The Anniversary Lectureship Scheme is designed to identify academic leaders of the future and attract the highest calibre of applicants with the potential to become Readers or Chairs within 5 years. You will not be allocated a direct teaching load in at least the first two years, although tutoring, project supervision and a small number of specialist lectures would be possible. In subsequent years you will remain research focussed but undertake appropriate teaching responsibilities to satisfy operational and promotion criteria.

For further information on the benefits of the 50th Anniversary Lectureship Scheme please visit

The School of Computing and Communications offers a highly inclusive and stimulating environment for career development, and you will be exposed to a range of further opportunities over the course of this post. We are committed to family-friendly and flexible working policies on an individual basis, as well as the Athena SWAN Charter, which recognises and celebrates good employment practice undertaken to address gender equality in higher education and research.

For further information or to arrange an informal discussion please contact:

Lancaster University - ensuring equality of opportunity and celebrating diversity

Location: Lancaster
Salary: £35,210 to £48,676
Hours: Full Time
Contract Type: Permanent
Placed On: 19th February 2019
Closes: 25th March 2019
Job Ref: A2561
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