Lancaster University | Senior Research Associate/Research Associate: Collaborative Technologies in Underwater Robotics and Computer Vision | Lancaster, UK | Onsite
A research position is available to work on an exciting, cross-disciplinary million pound project with a team of industrial partners (including QinetiQ, Nuvia, Bristol Maritime Robotics Ltd and Fortis Mechanical Design Ltd) funded by Innovate UK to investigate and develop next generation autonomous robotic systems that will operate in hazardous underwater environment with little direct human involvement. The research challenges include development of the situation awareness using tactile and passive EO sensors, navigation using sonar SLAM and decision making with elements of autonomy and objects recognition in challenging environments from sonar images using newly developed transparent/interpretable deep learning for advanced computer vision. Simulations will be performed using ROS and programming will be with Python (C or Matlab may also be considered for some developmental steps, but the expertise with Python and ROS is critically important).
In the project you will collaborate with an experienced team of industrial experts and will be performing challenging research tasks leading to the implementation of advanced algorithms on software (Python), testing and validating the results in simulation (in ROS) and ultimately on laboratory scale mobile robots (unmanned ground based vehicles). The results will be integrated in systems with industrial significance and national importance.
You will be an expert in the area of mobile robotics, autonomous systems, control and navigation with interest to SLAM and decommissioning and keen to learn more about computer vision and transparent deep learning.
We are particularly interested in applicants who are excited by the potential of working at the interface between disciplines.
A PhD degree (or being in a process of submission of a PhD) or equivalent in Computer Science or Engineering or a closely-related field is required to be eligible for this position. You will have a track record of high-quality publications in the areas of relevance to the project and the willingness to undertake ambitious and challenging research. For more details, please see the detailed Job Descriptions/Person Specifications for these positions.
A research position is available to work on an exciting, cross-disciplinary million pound project with a team of industrial partners (including QinetiQ, Nuvia, Bristol Maritime Robotics Ltd and Fortis Mechanical Design Ltd) funded by Innovate UK to investigate and develop next generation autonomous robotic systems that will operate in hazardous underwater environment with little direct human involvement. The research challenges include development of the situation awareness using tactile and passive EO sensors, navigation using sonar SLAM and decision making with elements of autonomy and objects recognition in challenging environments from sonar images using newly developed transparent/interpretable deep learning for advanced computer vision. Simulations will be performed using ROS and programming will be with Python (C or Matlab may also be considered for some developmental steps, but the expertise with Python and ROS is critically important).
In the project you will collaborate with an experienced team of industrial experts and will be performing challenging research tasks leading to the implementation of advanced algorithms on software (Python), testing and validating the results in simulation (in ROS) and ultimately on laboratory scale mobile robots (unmanned ground based vehicles). The results will be integrated in systems with industrial significance and national importance.
You will be an expert in the area of mobile robotics, autonomous systems, control and navigation with interest to SLAM and decommissioning and keen to learn more about computer vision and transparent deep learning.
We are particularly interested in applicants who are excited by the potential of working at the interface between disciplines.
A PhD degree (or being in a process of submission of a PhD) or equivalent in Computer Science or Engineering or a closely-related field is required to be eligible for this position. You will have a track record of high-quality publications in the areas of relevance to the project and the willingness to undertake ambitious and challenging research. For more details, please see the detailed Job Descriptions/Person Specifications for these positions.
https://hr-jobs.lancs.ac.uk/Vacancy.aspx?ref=A2682-R