Research Associate in Imaging and Learning for Realistic Appearance Modelling
The Department of Computing is a leading department of Computer Science among UK Universities, and has consistently been awarded the highest research rating. In the 2014 REF assessment, the Department was ranked third (1st in the Research Intensity table published by The Times Higher), and was rated as "Excellent" in the previous national assessment of teaching quality. We seek a Research Associate to work as part of a project led by Dr...
Job listing information
- Reference ENG00769
- Date posted 19 March 2019
- Closing date 14 May 2019
The Department of Computing is a leading department of Computer Science among UK Universities, and has consistently been awarded the highest research rating. In the 2014 REF assessment, the Department was ranked third (1st in the Research Intensity table published by The Times Higher), and was rated as "Excellent" in the previous national assessment of teaching quality.
We seek a Research Associate to work as part of a project led by Dr Abhijeet Ghosh in the areas of realistic computer graphics and imaging. The goal of the project is to investigate novel imaging, modelling, simulation and machine learning (ML) techniques for appearance of real world materials including bio-physical/spectral models of absorption and scattering of light in organic media such as human skin, as well as wave optical effects such as polarization, diffraction or interference effects in material reflectance.
Duties and responsibilities
The position offers an exciting opportunity for conducting internationally leading and impactful research, which aims to solve real-world problems in acquisition and modelling of materials, objects and scenes at the boundary of graphics, optics, imaging, and ML. There will also be an opportunity to work with PhD and MSc students and potentially co-supervise student projects, as well as access to a state-of-the-art multispectral Lightstage for appearance measurements.
Within the project, the Research Associate will be responsible for designing measurement protocols and software pipelines for data acquisition and processing for appearance modelling/analysis and evaluating results against ground truth, as well as developing deep learning algorithms and pipelines for appearance inference using training data obtained from measurements. They will be expected to publish their research results at leading venues in computer graphics, vision or applied optics.
To apply for this position, you will need to have a strong computer graphics and mathematics background. Some background in optics, computer vision or deep learning is also highly desirable. You should also have experience, including a proven publication track-record, in one or more of the following areas: appearance modelling, rendering, acquisition/imaging, deep learning. Preference will be given to candidates with prior experience in several of the following: C++/Python, OpenGL/CUDA, Matlab, OpenCV, DSLR/machine-vision cameras, raytracing/rendering, TensorFlow/PyTorch.
You must have a PhD (or equivalent experience and/or qualifications) in an area pertinent to the subject area, i.e. Computing or Engineering. You must be able to organise your own work and prioritise work to meet deadlines. All applicants must have excellent written and verbal communication skills. You will be part of the Realistic Graphics and Imaging research group.
For further information on the group, see: http://wp.doc.ic.ac.uk/rgi/
*Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant within the salary range £34,397 to £37,486 per annum.
Informal inquiries related to the position should be directed to Dr Abhijeet Ghosh: firstname.lastname@example.org
In addition to completing the online application, candidates should attach:
- A full CV
- A two-page research statement indicating what you see are interesting research issues relating to the above post and why your expertise is relevant.
For any queries regarding the application process please contact Jamie Perrins: email@example.com
About Imperial College London
Imperial College London is the UK’s only university focussed entirely on science, engineering, medicine and business and we are consistently rated in the top 10 universities in the world.
You will find our main London campus in South Kensington, with our hospital campuses located nearby in West and North London. We also have Silwood Park in Berkshire and state-of-the-art facilities in development at our major new campus in White City.
We work in a multidisciplinary and diverse community for education, research, translation and commercialisation, harnessing science and innovation to tackle the big global challenges our complex world faces.
It’s our mission to achieve enduring excellence in all that we do for the benefit of society – and we are looking for the most talented people to help us get there.
Please note that job descriptions cannot be exhaustive and the post-holder may be required to undertake other duties, which are broadly in line with the above key responsibilities.
All Imperial employees are expected to follow the 7 principles of Imperial Expectations:
- Champion a positive approach to change and opportunity
- Communicate regularly and effectively within, and across, teams
- Consider the thoughts and expectations of others
- Deliver positive outcomes
- Encourage inclusive participation and eliminate discrimination
- Develop and grow skills and expertise
- Work in a planned and managed way
In addition to the above, employees are required to observe and comply with all College policies and regulations.
Imperial College is committed to equality of opportunity, to eliminating discrimination and to creating an inclusive working environment. We are an Athena SWAN Silver award winner, a Stonewall Diversity Champion, a Disability Confident Employer and work in partnership with GIRES to promote respect for trans people.
Athena SWAN Silver Award 2016
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Imperial is a Disability Confident leader
Imperial is working in partnership with GIRES to promote respect and provide equal treatment for trans people