PhD Studentships in Agri-Robotics and Autonomous Terrestrial Mining

Several PhD opportunities with L-CAS are available to apply to. For further details and to apply go to

PhD Studentships in Agri-robot based High-throughput Phenotyping

Applications are invited for fully-funded three-year PhD studentships (2 positions) within Lincoln Agri-Robotics (LAR), the world’s first global centre of excellence in agricultural robotics, recently funded by UKRI’s Research England. This exciting centre bridges and expands the strong collaborations that exist between two leading research groups at the University of Lincoln: the Lincoln Institute for Agri-Food Technology (LIAT) and the Lincoln Centre for Autonomous Systems (L-CAS).

Using new and developing agri-robotic platforms and working alongside robotics researchers, students will work on crop science projects and contribute towards major challenges that face the global agri-food industry: high-throughput phenotyping, large-scale germplasm screening, big data management, precision agriculture, resource use efficiency and climate change.

Students will focus their research within the grand challenges prioritised by LAR in crop science, primarily focusing on high throughput phenotyping (HTP), e.g. gathering HTP data using multiple novel and traditional sensors such as hyperspectral, multispectral, and thermal imaging, LiDAR, and chlorophyll fluorescence imaging. Students will optimise sensor systems integrated on agri-robotic platforms for HTP field phenotyping in wheat. This research will identify best approaches in data collection, processing and analysis for phenotyping data including point cloud matrices, 3D reconstruction, and extraction of traits of interest using suitable programming languages such as R, Python and/or MATLAB. Students will gain knowledge and experience in development and implementation of research projects, HTP using agri-robots, crop image analysis, programming skills, field and controlled crop studies, and evaluating systems with end-users.

Our fully-funded studentship package includes:

  • All PhD tuition fees paid
  • A tax-free stipend to cover living costs
  • A Research Training Support Grant (RTSG)
  • Additional funding to support outreach and dissemination, attendance at summer schools, research events, and development projects.

Students can also benefit from:

  • The opportunity to develop their career, working alongside and in collaboration with academic and industry specialists of the future.
  • Internships, project work, and engagement opportunities with world-leading companies who are interested in both research collaboration and future postdoctoral graduates.
  • LAR PhD students will have the opportunity to study alongside students in the EPSRC Centre for Doctoral Training in Agri-Food Robotics (AgriFoRwArdS), led by the University of Lincoln in collaboration with the universities of Cambridge and East Anglia.

PhD Studentship in Autonomous Terrestrial Mining Robot

GMVIS skysoft, S.A. | ESA Business ApplicationsThis PhD studentship, fully funded by the University of Lincoln, falls within the framework of Robotics and Autonomous Systems (RAS) – one of the eight great technologies identified by the UK Government. This project is a collaborative initiative by the University of Lincoln and GMV, UK. The successful candidate will join the Lincoln Centre for Autonomous Systems (L-CAS), which is the University of Lincoln’s cross-disciplinary research group in robotics.  L-CAS specialises in technologies for perception, learning, decision-making, control and interaction in autonomous systems, especially mobile robots and robotic manipulators, and the integration of these capabilities for multi-sector applications. The project will be carried out in the School of Engineering and in partnership with the School of Computer Science.

The project aims at developing a new 3D volumetric mapping instrument based on vision. The instrument shall consist of two Intel RealSense D435 camera, a pan and tilt unit or similar and variable illumination. The project shall focus on the design of a novel pan and tilt unit or similar mechanism fulfilling the requirements, the design of a variable illumination light array and novel software using stereo imaging and variable illumination to create accurate volumetric maps in an underground environment.

In collaboration with GMV UK, this study will contribute to the ongoing Innovate UK funded Autonomous Robotic InSpEction (ARISE) project, which aims to implement autonomous surveys of geotechnical conditions during the normally unproductive period immediately after the blast; this is when workers vacate the mine due to post-blasting fumes and seismic risk. The robotic platform will be used to:

  1. Survey roof conditions in newly-blasted areas;
  2. Monitor material flow in ore passes and extraction points, particularly mapping ‘hangups’ that can block ore passes. Mapping hangups from below is extremely dangerous for people;
  3. Accurately map areas in 3D for reconciliation and design verification.
  4. ARISE will provide safety and financial benefits while not affecting the production cycle (operating in the shift change periods) and is therefore attractive for industrial roll-out.

The student will have an opportunity to interact with the ARISE Consortium, undertake site visits, access field trial data and participate in field trial depending on scheduling.