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11803- Research Associate in Artificial Intelligence for Autonomous Vehicles
| Dyddiad hysbysebu: | 30 Ebrill 2025 |
|---|---|
| Cyflog: | £40,497 i £48,149 bob blwyddyn |
| Oriau: | Llawn Amser |
| Dyddiad cau: | 28 Mai 2025 |
| Lleoliad: | Edinburgh, Scotland |
| Gweithio o bell: | Ar y safle yn unig |
| Cwmni: | University of Edinburgh |
| Math o swydd: | Dros dro |
| Cyfeirnod swydd: | 11803 |
Crynodeb
UE07: £40,497.00 - £48,149.00 Per Annum.
CSE / School of Informatics.
Fixed Term Contract - 2 Years.
Full Time - 35 Hours Per Week.
The Opportunity:
This post will be part of the Centre for AI for Assistive Autonomy, a mission-driven research centre established using a UKRI Turing AI World Leading Researcher Fellowship awarded to Prof Subramanian Ramamoorthy.
The post-holder will be the lead researcher anchoring laboratory activities in the area of Artificial Intelligence for autonomous vehicles, with a focus on human-centred settings including shared autonomy and autonomous operation in crowded urban environments. This represents one of the main application themes within the centre, alongside assistive technology in healthcare domains. This work benefits from parallel work of a foundations team, whose focus will be on fundamental investigations into generative modelling of the full stack of human behaviour, from sensorimotor control to higher level cognitive decision making, to enable the development of person-centred and teachable autonomous systems.
The post holder will be supervised by the Centre Director (Ramamoorthy). The post holder will also have the opportunity to collaborate with colleagues in a wide range of specialties across the University, including in machine learning and vision (e.g. Fisher, Mac Aodha, Bilen, Sevilla-Lara, Vergari), probabilistic programming (e.g. Narayanaswamy, Kammar, Belle), natural language understanding and interaction (e.g. Lascarides, Lapata, Gal), computational cognitive science and neuroscience (e.g. Lucas, Hennig, Nolan, Rajendran), as well as in robotics and neurotechnology (e.g. Vijayakumar, Nazarpour) and engineering of novel sensing and devices (Prodromakis, Koutsos, Amjadi). Beyond the university, the Centre will pursue collaborations with international teams including at The University of Texas at Austin (Stone), Stanford University (Kochenderfer), University of Bremen (Beetz) and Monash University (Burke).
The Centre will also have a strong industrial partner network, including Fourier Intelligence, Honda Research Europe, Shadow Robot, Sony Europe and other organisations who will be engaged in the Centre’s work at all stages, with the expectation that this network grows over time as the Centre’s work grows and begins to have broader impacts.
The central purpose of the job is to investigate human-centred AI methods to enable novel applications including shared autonomy and autonomous operation in crowded urban environments.
This work builds on an established track record with autonomous systems that been deployed in field trials within Five (a Bosch company). Following this earlier work and an equipment donation to establish new laboratory facilities, this post holder will be a crucial part of a new initiative within the university to explore emerging issues for next generation mobility systems. With the support of three research engineers who are part of this laboratory, we are undertaking efforts to create a novel Edinburgh dataset focussed on driving in dense urban environments, a resource that will be available for the post holder to build on.
The post holder will be expected to address a range of issues including the following:
Real-time perception for human intention and environmental state inference
Human-in-the-loop adaptation strategies for shared autonomy
Interactive decision making methods in urban driving environments
Planning and decision making in interactions involving vulnerable road users (pedestrians, cyclsists, etc.)
Large scale data-driven modelling of driver behaviour in urban environments
The candidate is expected to take intellectual ownership of core scientific questions in this space, developing new ideas and driving collaborative projects towards significant publications, leveraging the expertise of the supervision team and other scientific collaborators.
It is also expected that the post holder will contribute to the development of new assets in the form of experimental robotic systems and demonstrators. These will be expected to make use of data and model assets created by other Centre researchers.
Your skills and attributes for success:
Essential:
A PhD (or near completion) in AI and/or robotics, with a focus on autonomous vehicles applications
An excellent track record of publications in top-tier journals (e.g. IEEE Trans. or broad-interest science venues) and/or conferences in AI (e.g. IJCAI, AAAI, NeurIPS, ICML, ICLR), robotics (e.g. R:SS, CoRL, ICRA), or allied areas
Excellent proven experience of developing field robotics systems
Ability to work effectively as part of a team, to meet deadlines, and to report on project progress
Ability to communicate complex information clearly, orally and in writing.
Desirable:
Research experience with methods for learning and decision making in sequential decision making problems with humans in the loop
Research experience with real-time perception and scene understanding methods based on state-of-the-art machine learning methods
Hands-on experience of designing and conducting field experiments, including human subject studies
Demonstrated experience of the development and management of projects involving multiple stakeholders.
CSE / School of Informatics.
Fixed Term Contract - 2 Years.
Full Time - 35 Hours Per Week.
The Opportunity:
This post will be part of the Centre for AI for Assistive Autonomy, a mission-driven research centre established using a UKRI Turing AI World Leading Researcher Fellowship awarded to Prof Subramanian Ramamoorthy.
The post-holder will be the lead researcher anchoring laboratory activities in the area of Artificial Intelligence for autonomous vehicles, with a focus on human-centred settings including shared autonomy and autonomous operation in crowded urban environments. This represents one of the main application themes within the centre, alongside assistive technology in healthcare domains. This work benefits from parallel work of a foundations team, whose focus will be on fundamental investigations into generative modelling of the full stack of human behaviour, from sensorimotor control to higher level cognitive decision making, to enable the development of person-centred and teachable autonomous systems.
The post holder will be supervised by the Centre Director (Ramamoorthy). The post holder will also have the opportunity to collaborate with colleagues in a wide range of specialties across the University, including in machine learning and vision (e.g. Fisher, Mac Aodha, Bilen, Sevilla-Lara, Vergari), probabilistic programming (e.g. Narayanaswamy, Kammar, Belle), natural language understanding and interaction (e.g. Lascarides, Lapata, Gal), computational cognitive science and neuroscience (e.g. Lucas, Hennig, Nolan, Rajendran), as well as in robotics and neurotechnology (e.g. Vijayakumar, Nazarpour) and engineering of novel sensing and devices (Prodromakis, Koutsos, Amjadi). Beyond the university, the Centre will pursue collaborations with international teams including at The University of Texas at Austin (Stone), Stanford University (Kochenderfer), University of Bremen (Beetz) and Monash University (Burke).
The Centre will also have a strong industrial partner network, including Fourier Intelligence, Honda Research Europe, Shadow Robot, Sony Europe and other organisations who will be engaged in the Centre’s work at all stages, with the expectation that this network grows over time as the Centre’s work grows and begins to have broader impacts.
The central purpose of the job is to investigate human-centred AI methods to enable novel applications including shared autonomy and autonomous operation in crowded urban environments.
This work builds on an established track record with autonomous systems that been deployed in field trials within Five (a Bosch company). Following this earlier work and an equipment donation to establish new laboratory facilities, this post holder will be a crucial part of a new initiative within the university to explore emerging issues for next generation mobility systems. With the support of three research engineers who are part of this laboratory, we are undertaking efforts to create a novel Edinburgh dataset focussed on driving in dense urban environments, a resource that will be available for the post holder to build on.
The post holder will be expected to address a range of issues including the following:
Real-time perception for human intention and environmental state inference
Human-in-the-loop adaptation strategies for shared autonomy
Interactive decision making methods in urban driving environments
Planning and decision making in interactions involving vulnerable road users (pedestrians, cyclsists, etc.)
Large scale data-driven modelling of driver behaviour in urban environments
The candidate is expected to take intellectual ownership of core scientific questions in this space, developing new ideas and driving collaborative projects towards significant publications, leveraging the expertise of the supervision team and other scientific collaborators.
It is also expected that the post holder will contribute to the development of new assets in the form of experimental robotic systems and demonstrators. These will be expected to make use of data and model assets created by other Centre researchers.
Your skills and attributes for success:
Essential:
A PhD (or near completion) in AI and/or robotics, with a focus on autonomous vehicles applications
An excellent track record of publications in top-tier journals (e.g. IEEE Trans. or broad-interest science venues) and/or conferences in AI (e.g. IJCAI, AAAI, NeurIPS, ICML, ICLR), robotics (e.g. R:SS, CoRL, ICRA), or allied areas
Excellent proven experience of developing field robotics systems
Ability to work effectively as part of a team, to meet deadlines, and to report on project progress
Ability to communicate complex information clearly, orally and in writing.
Desirable:
Research experience with methods for learning and decision making in sequential decision making problems with humans in the loop
Research experience with real-time perception and scene understanding methods based on state-of-the-art machine learning methods
Hands-on experience of designing and conducting field experiments, including human subject studies
Demonstrated experience of the development and management of projects involving multiple stakeholders.