Research Assistant in Robust Perception

Queen Mary University of London; Greater London; On-site; GBP 40,000 - 60,000; Full time

Job summary

A prestigious UK university is seeking a researcher to investigate AI-based automotive perception. The role involves developing methodologies for sensor analysis, collaborating with industry partners, and publishing research findings. Candidates should have experience in automotive sensor data collection and ROS2. Competitive salaries, flexible working arrangements, and a commitment to diversity are offered.

Benefits

Competitive salary

Generous pension scheme

30 days' leave per annum

Flexible working arrangements

Professional development opportunities

Qualifications

• Experience in working with industry partners on research projects related to sensing and perception in automated vehicles.
• Expertise in automotive sensor data collection, ROS2, and DNN-based data enhancement.

Responsibilities

• Conduct in depth research into AI-based automotive perception.
• Develop methodologies for sensor modelling, noise factor analysis, and machine learning.
• Provide support to the ROADVIEW consortium and partner projects.
• Publish research outcomes in reputable journals and present findings at conferences.

Skills

Automotive sensor data collection

ROS2

DNN-based data enhancement

Job description

Responsibilities

• Conduct in depth research into AI based automotive perception and relationship with the quality of perception sensor data.
• 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.
• 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.
• 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.

Qualifications

You will need previous experience in working with industry partners on research projects related to sensing and perception in automated vehicles. In particular, you need to demonstrate expertise in automotive sensor data collection, ROS2, and expertise in perception (DNN-based) aware data enhancement.

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.

Diversity and Inclusion

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. 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.

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.