Fixed-term: The funds for this post are available for 7 months in the first instance.
A position is available to work on a project entitled "Co-Evolving Built Environments and Mobile Autonomy for Future Transport and Mobility", with a starting date between December 2018 and January 2019, for a duration of 7 months.
This project aims to provide new tools in support of a novel framework that facilitates the development of enhanced infrastructure for mobile autonomy in built environments. Specifically, we will develop methods that optimize the placement and configuration of sensor nodes for perceptive infrastructure in aid of autonomous mobile navigation in urban environments. The core research will consider sensor node placement strategies for an optimally enhanced infrastructure. Since classical combinatorial optimization methods are intractable for large-scale problems, the project will leverage tools from data science, machine learning and predictive analytics.
Essential requirements: Candidates should have a 1st class degree in computer science, engineering, mathematics or a closely related discipline, with experience and interest in one of the following areas: machine learning, optimization, mobile autonomy. Very good programming skills are required. If a candidate has a track record of publications, it should be included in the application as a link to a Google Scholar or ORCID profile.
The position is open to both UK/EU and non-EU applicants.
Applicants should contact Dr Amanda Prorok ( http://www.proroklab.org ) for further information.
To apply online for this vacancy, please click on the 'Apply' button below. This will route you to the University's Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form.
Please ensure you upload your Curriculum Vitae (CV), a covering letter, transcripts (BSc and MSc if completed) and the evidence of competence in English if English is not your first language.
If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.
Please quote reference NR17196 on your application and in any correspondence about this vacancy.
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