Research Associate (Fixed Term) (HC10603)

Job title Research Associate (Fixed Term)

Department Mechanical Engineering

Salary Starting from £36,333, rising to £43,155

Grade Grade 7

SOC Code - Visa Requirements 2119

This role is sponsorable

Placed on Friday 12 May 2023

Closing date Sunday 04 June 2023

Interview date To be confirmed

Reference HC10603

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The Department of Mechanical Engineering is seeking for a Research Associate.

Synthetic aperture sonar (SAS) is an advanced underwater acoustic imaging technology. SAS-equipped uncrewed underwater vehicles (UUVs) are able to perform detailed imaging of the seafloor with centimetre resolution at rapid coverage rates of square-kilometres per second. This wealth of detailed imagery necessitates machine learning (ML) to extract information relating to application use cases, such as unexploded ordnance remediation, benthic mapping, etc. While these data are abundant, they are not always diverse since the ocean floors are vast and only a tiny fraction has been explored in detail. Furthermore, they are not adequately labelled due to difficulty obtaining ground-truth knowledge of seafloor features and objects. This presents a challenge to deploying ML solutions, which typically require abundant, diverse, and labelled data. This project aims to address this challenge through simulation.

A recent breakthrough in SAS data simulation at the University of Bath has enabled rapid creation of synthetic data that accurately captures many of the important aspects of acoustic wave physics. This project will investigate how this new capability can be best leveraged in augmenting ML training. It will determine how the simulation realism affects ML performance and identify and develop aspects of the 3-D seafloor models (e.g., scene content, effects of underwater processes, etc.) and acoustic wave physics (propagation, scattering etc.) that are a necessity for good performance. Furthermore, it will explore the integration with the advanced ML methods of generative deep learning and reinforcement learning. This role is part of collaborative US- funded project with Pennsylvania State University (PSU). You will be leading the simulation work at the University of Bath and will work closely with ML experts at PSU.

This position is offered on a full time (36.5 hours per week) fixed term basis with an expected duration of 3 years.

We aim to be an inclusive university, where difference is celebrated, respected and encouraged. We have an excellent international reputation with staff from over 60 different nations and have made a positive commitment towards gender equality and intersectionality receiving a Silver Athena SWAN award. We truly believe that diversity of experience, perspectives, and backgrounds will lead to a better environment for our employees and students, so we encourage applications from all genders, backgrounds, and communities, particularly from under-represented groups, and value the positive impact that will have on our teams.

We are very proud to be an autism friendly university and are an accredited Disability Confident Leader; committed to building disability confidence and supporting disabled staff.

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Visa information

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Update to our application process

assessment process, with the goal of creating an inclusive and equal assessment process. To support this, personal details will be removed from application forms at the initial shortlisting stage.