Research Assistant in Learning Strategies for Robust DNNs

About the Role

You will be employed to work on our EU Horizon ROADVIEW project related to perception sensors, modelling, data collection and robust perception, in collaboration with industry and academic partners.

About You

You will need previous experience in engagement in research projects related to sensing and perception in automated vehicles. In particular, you need to demonstrate expertise in learning strategies and automotive datasets.

Key duties for the role are to conduct in depth research into AI based automotive perception and relationship with different learning strategies to optimize the learning process.

You will be able to develop novel and appropriate methodologies to support current research activities of the QMUL SPRING group (including: sensor modelling, noise factor analysis, machine learning, data pre-processing, fusion, etc.). This will require engagement with sector and subject matter specialists at all levels of employment to understand the current industry practice and latest international standards and legislative directives

You will be able to provide comprehensive directions and technical support to the ROADVIEW consortium and the partners on all aspects of the project. Deputise for the project manager at senior management meetings as required ensuring that appropriate input is given and outcomes are reported to the project manager and others within the research team in a timely manner.

You will be able to support the publication of research outcomes in appropriate journals of international standing and to disseminate the result of research and scholarship in other reputable outlets. To attend and present research and project findings at professional conferences and contribute to the external visibility and profile of the department

About the School

This post is within the School of Engineering and Materials Science, a large School with 120 academics and 70 postdoctoral research staff. There are around 1371 undergraduate and postgraduate students and 233 PhD students. These are supported by an administrative and technical staff team of 56. The staff and student body are international in make-up. 

About Queen Mary

At Queen Mary University of London, we believe that a diversity of ideas helps us achieve the previously unthinkable.

Throughout our history, we’ve fostered social justice and improved lives through academic excellence. And we continue to live and breathe this spirit today, not because it’s simply ‘the right thing to do’ but for what it helps us achieve and the intellectual brilliance it delivers.

We continue to embrace diversity of thought and opinion in everything we do, in the belief that when views collide, disciplines interact, and perspectives intersect, truly original thought takes form.

Benefits

We offer competitive salaries, access to a generous pension scheme, 30 days’ leave per annum (pro-rata for part-time/fixed-term), a season ticket loan scheme and access to a comprehensive range of personal and professional development opportunities. In addition, we offer a range of work life balance and family friendly, inclusive employment policies, flexible working arrangements, and campus facilities.

Queen Mary’s commitment to our diverse and inclusive community is embedded in our appointments processes. Reasonable adjustments will be made at each stage of the recruitment process for any candidate with a disability. We are open to considering applications from candidates wishing to work flexibly.

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