Research Scientist - Motion (Self Driving Vehicles)
Highly competitive package which includes BUPA and Stock options
I have an urgent requirement for a Research Scientist with my rapidly growing client within the autonomous vehicle sector. The role is based in Edinburgh and you would be joining a growing company and working within a team of world-class scientists and renowned academic advisers.
About the role
· Research and develop state-of-the-art large scale predictive models of dynamic road scene environments to produce rich predictions, dynamic cost maps and motion plans
· Apply novel prediction techniques such as inverse reinforcement learning (inverse optimal control) to generate those cost maps.
· Develop and improve ways of establishing beliefs in the goals and behaviours of actors in road scenes and develop and curate learnt behavioural model libraries
· Research and identify suitable methods of building memory into these models, for example using LSTMs and RNNs
· Explore and implement game theoretic approaches alongside reinforcement learning to predict interactive actor behaviour in road scenes and their likelihoods
· Find ways of using deep perception outputs to improve those predictions (gestures, pose, gaze, wheel movements etc) and identify means of feeding those requirements back to the perception layers of the run-time vehicle stack
· Select and develop path planning methodologies, likely based on variants of D*, A*, RRT* algorithms, which, together with kino-dynamic vehicle models, deliver feasible and preferred paths
· Generate novel research techniques for solving multiple challenges in the field of computer vision as applied to autonomous vehicles and work to get outputs published in the world's top scientific journals and conferences
· PhD graduate in the field of machine learning and/or artificial intelligence
· Masters-level graduate in a relevant field (computer science, mathematics, physics, statistics, engineering)
· At least one year of post-doctoral research and/or industry experience
· Track record of work being published in top scientific journals and/or being accepted at leading international conferences (eg IROS, AAAI, IJRR, NIPS, ICRA, MLJ, JMLR, HSR, EUMAS etc)
· Strong background in machine learning as applied to prediction
· Strong analytical background and deep understanding of large-scale optimization
· Strong programming skills (eg Python, C/C++, Scala, Matlab, Java) as well as LINUX, HTML and GPU programming including CUDA
To apply or for more information please contact Seamus Hayes at IC-Resources
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