[robotics-worldwide] [jobs] Research Fellow in AI for Autonomous Driving @ Oxford Brookes

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[robotics-worldwide] [jobs] Research Fellow in AI for Autonomous Driving @ Oxford Brookes

Fabio Cuzzolin
The School of Engineering, Computing and Mathematics at Oxford Brookes
University is seeking a Research Fellow in Artificial Intelligence for
Autonomous Driving, to be appointed as soon as possible, for a duration of
16 months. The Fellow will be appointed at Grade 8, with a starting salary
of £31,866 per annum, rising annually to £34,804.

The deadline for application is January 2 2020.

The successful candidate will lead the School’s effort towards the
development of human-aware AI for autonomous driving, and will be soon
joined by at least one PhD student.

The project concerns the design and development of novel ways for robots
and autonomous machines to interact with humans in a variety of emerging
scenarios, with a focus on autonomous driving. We believe novel, disruptive
applications of AI require neuroscience-inspired forms of communication
between humans and machines much beyond the current level of
sophistication. Smart cars need to understand that children and
construction workers have different reasoning processes that lead to very
different observable behaviour, in order to blend in with the road as a
human-centred environment. Morally and socially appropriate behaviour is
key to build trust and lead to acceptance from the public.

The Fellow will work to design and implement a prototype but complete
pipeline in a simulated scenario, including: (i) the design of theory of
mind simulations allowing smart cars to understand the reasoning and
intentions of other drivers and pedestrians; (ii) the making of decisions
based on the results of these simulations; (iii) the actual control and
path planning required to pursue the best course of action, with
demonstration in a simulated environment.

They will also coordinate the efforts of the three groups in the area by
supervising MSc and final year students working on the subject, and
liaising with our partners in Oxford, Cambridge and elsewhere.

As the project concerns artificial intelligence, mobile robotics and
engineering aspects, the Fellow will work jointly with the Visual
Artificial Intelligence, Cognitive Robotics and Autonomous Driving research
groups, led by Prof Fabio Cuzzolin, Dr Matthias Rolf and Dr Andrew Bradley.
The Visual Artificial Intelligence Laboratory (
https://urldefense.proofpoint.com/v2/url?u=http-3A__cms.brookes.ac.uk_staff_FabioCuzzolin_&d=DwIFaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=s3fIctXYgAO2DielKkUljtz5IPpDMarmhktgqEN8ItM&s=C_2MV3aiOAH1QdGyQxNTPBRaE8f4IwNS8gSbsXrjsyk&e= ) is a thriving unit projected
to comprise 25+ members in 2019, which has established itself as one of the
top research groups in the world in deep learning for action detection,
conducting work at the current boundaries of human action recognition.

The Engineering section has a strong reputation in motorsports and
engagement with F1 teams, as demonstrated by Oxford Brookes Racing having
been crowned Class 1 Runner Up in the 2018 Formula Student competition. The
three groups can provide equipment including a network of GPU servers for a
total of around 30 cards, a significant number of humanoid robots (NAO,
Baxter, Robothespian) as well as autonomous driving equipment and software.

In 2019 Oxford Brookes, led by Bradley and assisted by Cuzzolin, came 3rd
place overall in the first edition of the IMEC-sponsored Formula Student –
AI competition:


A new dataset in Road Event and Activity Detection (RoAD), the first in the
world of its kind, is in the process of being released as a challenge to
IROS 2020 and ECCV 2020 (https://urldefense.proofpoint.com/v2/url?u=https-3A__arxiv.org_abs_1807.11332&d=DwIFaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=s3fIctXYgAO2DielKkUljtz5IPpDMarmhktgqEN8ItM&s=8GrruF7dWmppKHVRl-Ck0nYvcQFms4ACZXeFrSzAt8U&e= ).

You are encouraged to contact Prof Cuzzolin at [hidden email]
for more information and informal feedback on your application.

To formally apply, please follow the instructions provided here:

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[hidden email]