Research Associate in Underwater Scene Representation

This role will work on the specific project “MyUnderwaterWorld: Intelligent Underwater Scene Representation” funded by MyWorld and EPSRC International Collaboration grant. Our international partners include National Park Service Submerged Resources Center (USA), Woods Hole Oceanographic Institute (USA), Marine Imaging Technologies (USA), National Oceanic and Atmospheric Administration (USA), Gates Underwater Products (USA), and Esprit Film & Television (UK).

Underwater environment represents the combination of several challenges. Water is a dynamic medium and suspended particles move. Light scatter causes blur and halo effects, whilst light absorption leads to colour distortion and reduced contrast. The model of underwater imagery should thus comprise temporally- and spatially-variant distortion, uneven intensity bias, multiplicative noise, and additive noise. This project aims to exploit underwater image priors to perform 3D mapping process can be done directly from the raw underwater sequences. Analysis will then be used to develop a new method for 3D representation of complex underwater scenes by optimising an underlying continuous volumetric scene function and merging with SLAM techniques to cover a large area with high definition at areas of interest.

Research Responsibilities

The role will deliver:

• Tools for analysis, restoration and enhancement of videos degraded by underwater distortions based on various machine learning methods;
• Tools for 3D modelling and representation for underwater scene;
• An assessment of the performance and utility of the tools produced;
• To document the work carried out and assist in training colleagues how to use the tools;
• Publish findings in the high impact journal and international conferences

Administration Responsibilities

The post holder will be expected to contribute to the organisation of activities, including those associated with the programmes mentioned above.

Teaching Responsibilities

There will be opportunities for the post holder to undertake project supervision at UG/PGT level, particularly related to our BEng/MEng programmes in Computer Science and our MSc in Immersive Technologies (AR/VR), and to contribute to the development and delivery of short courses within the MyWorld programme.

Essential

• A strong research track record in image processing; and/or 3D modelling; and/or in machine learning with application to image enhancement problems and an ability to innovate.
• Proven research experience in image processing and in machine learning and/or related areas.
• Strong project management skills.
• A commitment to share knowledge in an enthusiastic and effective manner.

Desirable

• Proven ability to publish papers in top venues relevant to the area of research.
• Experience in delivering successful research projects.
• A proven track record of collaborating with both academic and industrial partners.

For informal queries please contact Dr Pui Anantrasirichai, [email protected] .

To find out more about what it's like to work in the Faculty of Engineering, and how the Faculty supports people to achieve their potential, please see our staff blog:

https://engineeringincludesme.blogs.bristol.ac.uk/

Interviews are anticipated to be held on 19 March 2024.

We recently launched our strategy  to 2030 tying together our mission, vision and values.

The University of Bristol aims to be a place where everyone feels able to be themselves and do their best in an inclusive working environment where all colleagues can thrive and reach their full potential. We want to attract, develop, and retain individuals with different experiences, backgrounds and perspectives – particularly people of colour, LGBT+ and disabled people - because diversity of people and ideas remains integral to our excellence as a global civic institution.

This role will work on the specific project “MyUnderwaterWorld: Intelligent Underwater Scene Representation” funded by MyWorld and EPSRC International Collaboration grant. Our international partners include National Park Service Submerged Resources Center (USA), Woods Hole Oceanographic Institute (USA), Marine Imaging Technologies (USA), National Oceanic and Atmospheric Administration (USA), Gates Underwater Products (USA), and Esprit Film & Television (UK).

Underwater environment represents the combination of several challenges. Water is a dynamic medium and suspended particles move. Light scatter causes blur and halo effects, whilst light absorption leads to colour distortion and reduced contrast. The model of underwater imagery should thus comprise temporally- and spatially-variant distortion, uneven intensity bias, multiplicative noise, and additive noise. This project aims to exploit underwater image priors to perform 3D mapping process can be done directly from the raw underwater sequences. Analysis will then be used to develop a new method for 3D representation of complex underwater scenes by optimising an underlying continuous volumetric scene function and merging with SLAM techniques to cover a large area with high definition at areas of interest.

Research Responsibilities

The role will deliver:

• Tools for analysis, restoration and enhancement of videos degraded by underwater distortions based on various machine learning methods;
• Tools for 3D modelling and representation for underwater scene;
• An assessment of the performance and utility of the tools produced;
• To document the work carried out and assist in training colleagues how to use the tools;
• Publish findings in the high impact journal and international conferences

Administration Responsibilities

The post holder will be expected to contribute to the organisation of activities, including those associated with the programmes mentioned above.

Teaching Responsibilities

There will be opportunities for the post holder to undertake project supervision at UG/PGT level, particularly related to our BEng/MEng programmes in Computer Science and our MSc in Immersive Technologies (AR/VR), and to contribute to the development and delivery of short courses within the MyWorld programme.

Essential

• A strong research track record in image processing; and/or 3D modelling; and/or in machine learning with application to image enhancement problems and an ability to innovate.
• Proven research experience in image processing and in machine learning and/or related areas.
• Strong project management skills.
• A commitment to share knowledge in an enthusiastic and effective manner.

Desirable

• Proven ability to publish papers in top venues relevant to the area of research.
• Experience in delivering successful research projects.
• A proven track record of collaborating with both academic and industrial partners.

For informal queries please contact Dr Pui Anantrasirichai, [email protected] .

To find out more about what it's like to work in the Faculty of Engineering, and how the Faculty supports people to achieve their potential, please see our staff blog:

https://engineeringincludesme.blogs.bristol.ac.uk/

Interviews are anticipated to be held on 19 March 2024.

We recently launched our strategy  to 2030 tying together our mission, vision and values.

The University of Bristol aims to be a place where everyone feels able to be themselves and do their best in an inclusive working environment where all colleagues can thrive and reach their full potential. We want to attract, develop, and retain individuals with different experiences, backgrounds and perspectives – particularly people of colour, LGBT+ and disabled people - because diversity of people and ideas remains integral to our excellence as a global civic institution.