Connectionists: Machine Learning and Computer Vision Research Scientist (KTP Associate) - London, UK

[Bjørn Sand Jensen]

As part of a 34 month Knowledge Transfer Partnership funded by Innovate UK between the Schools of Psychology and Computing Science at University of Glasgow and the company Qumodo in London we are looking to hire a Knowledge Transfer Associate.

The aim of the project is to develop, deploy and commercialise an robust and reliable image Location Identification Classifier (LoID) to match large volumes of images, based on scene, metadata, and location content, utilising computer vision and machine learning. This technology will be used by Qumodo customers in policing and security to identify and protect child victims of abuse. The successful delivery of this project will assist investigators and contribute to a safer society.

The associate will spend the majority of their time in *London* working at the Qumodo facility and receive supervision on the University of Glasgow side by Frank Pollick (psychology), and Paul Siebert and Bjørn Sand Jensen (computing science). Further details are below and in the posting at: https://www.jobs.ac.uk/job/CAC519/machine-learning-and-computer-vision-research-scientist-ktp-associate .

Please contact (frank.pollick at glasgow.ac.uk) if you would have any questions. *The application deadline is 18 June 2020.*

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We are looking for a Machine Learning Research Scientist to work on a Knowledge Transfer Partnership (KTP) funded project with the aim to develop and commercialise an image Location Identification Classifier (LoID) to match large volumes of images, based on scene, metadata, and location content, utilising computer vision and machine learning. This technology will be used by Qumodo customers in policing and security to identify and protect child victims of abuse. The successful delivery of this project will assist investigators and contribute to a safer society.
The industrial partner for this project is Qumodo (qumo.do). Qumodo specialises in research and development related to human interaction with AI, primarily for applications which help to build a safer society. The selected candidate will primarily be based at their premises in London receiving training from both the company and university teams.
The candidate should have a strong programming background and experience with machine learning, computer vision, running a research project and experimental design. Their work will be aligned to the commercial interests of the company and they will work collaboratively with the company's Research and Development team, taking an instrumental role in the delivery of new products. The successful candidate will also be expected to write reports on their studies and research papers during the course of the KTP.
It is highly desirable that candidates are eligible for UK security clearance and have been resident in the UK for at least five years.
The salary shall be determined by the Researcher, the University and the KTP Partner. The amount shall be appropriate to the experience and qualifications of the appointed Researcher in the region of £33,000 - £45,000 per annum depending on qualifications and experience.
Funding is available on a full-time basis (35 hours per week) and is available for up to 34 months in the first instance.
For further enquiries about the role please contact:

Prof. Frank Pollick (Principal Investigator) - Frank.Pollick at glasgow.ac.uk
Dr. Paul Siebert (computer vision) - Paul.Siebert at glasgow.ac.uk
Dr. Bjørn Sand Jensen (machine learning) - Bjorn.Jensen at glasgow.ac.uk

For more information and to apply online, click https://my.corehr.com/pls/uogrecruit/erq_jobspec_version_4.jobspec?p_id=038077

Closing Date: 18 June 2020.

It is the University of Glasgow’s mission to foster an inclusive climate, which ensures equality in our working, learning, research and teaching environment. We strongly endorse the principles of Athena SWAN, including a supportive and flexible working environment, with commitment from all levels of the organisation in promoting gender equality. The University of Glasgow, charity number SC004401.

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