Find out more about our CDT programme
Our 4 year training programme has been created by our team of world-leading geospatial scientists.
In partnership with
PHD RESEARCHERS
CDT Programme
The CDT four year (1+3) training programme has been created by our team of world-leading geospatial scientists, informed by our industry partners, and is delivered at state of the art facilities at Newcastle University and the University of Nottingham. Upon completion of training with the CDT, students will developed technical skills and industry focused knowledge that can be applied to;
• Urban and Infrastructure Resilience
• Spatially Informed Mobility
• Spatially Engineered Energy Systems
• Long term sustainable Spatial Planning
• Multi-Scale Structural Monitoring
• Social Inclusion and Healthy Living
• Translation to Global Challenges
ABOUT
Funding and Placements
CDT PhD students will receive full fees and an annual living allowance which is based on the UKRI rate (rate for 2022/23, £17,668). A substantive Research Training Support Grant (RTSG) to cover the costs for consumables, travel, conferences, and access to placement opportunities with industrial partners.
Programme STRUCTURE
Everything you need to know about the course
In year one, students will undertake an MRes in Geospatial Data Science. Although students predominantly study at their host institution, the programme also consists of several joint modules which requires students across both institutions working together. Toward the end of the MRes, students will start forming their PhD research proposal and selecting a supervision team.
The MRes has been designed around the five CDT research themes and will also include a group project and individual research project.
Spatial Statistics
Statistics is a fundamental discipline in data science, this topic will introduce Students to the theory and practical application of modern statistical approaches for data handling and analysis, including the use of statistical software (e.g., R).
Big Data Spatial Analytics
Students will learn the fundamentals of Big Data data capture, management, analysis and programming. The module(s) will also introduce students to technology that is increasingly important in Geospatial Systems research, such as NoSQL databases, cloud computing and real-time Big Data analytics.
Spatial Analysis and Modelling
Students will extend their statistical knowledge and skills within the spatial analysis and modelling theme; covering spatial statistics and the theory and applied use of spatial simulation models (spatial equilibrium models, microsimulation, agent-based modelling (ABM)). The increasingly importance of AI, and in particular machine learning, for geospatial data analysis is recognised by further study where students will study supervised learning methods, cluster analysis, deep learning and feature extraction approaches.
Visualisation and Decision Support
Students will receive training in the modern methods of spatial data visualisation, such as virtual and augmented reality, and develop skills on how to deliver and present the outputs of geospatial data analysis and modelling; skills required to ensure that objective decisions and choices are made when using geospatial information.
Responsible Research and Innovation
Understanding the ethical, legal and social impact of the many different types of geospatial data now routinely collected (satellite, drones, social media, IoT and sensor networks) is critically important. To ensure a geospatially focused consideration of these important issues, all students will take a jointly delivered module on Understanding Geospatial Data: Social, Legal and Ethical Perspectives in Semester 2 at Newcastle.
In addition to formal taught lectures, this module will include a series of talks and seminars from industry, geospatial organisations so that students gain an excellent understanding of not only the theory behind the social, ethical and legal aspects of geospatial data, but also the practicalities of how this is delivered.
Group Project
Students will undertake a group project that aims to integrate the knowledge gained and practical skills developed in the taught modules. Each group will work on a small but real-world problem which will require groups to integrate and utilise their learning from the geospatial data, analytics, modelling and visualisation modules, along with the computing and statistical skills acquired.
The group project will start with a three-day joint workshop, where the project challenge will be presented, and initial group activity undertaken along with appropriate academic mentoring.
Dissertation in Geospatial Data Science
The individual dissertation is a significant piece of independent work where the concepts and skills acquired in earlier modules is applied to a technical or applied piece of work. It will allow the development of specialist and specific knowledge and skills that relate directly to wider research interests. The dissertation will involve working closely with an appropriate supervision team and in many cases will offer the opportunity to engage and work with geospatial industry experts.
Upon successful completion of the MRes, during years 2-4 students will transfer and register on a PhD with their host insitution to conduct interdisciplinary research into smart cities, infrastructure resilience, spatial mobility, energy systems, sustainable spatial planning, social inclusion, global challenges or other geospatial application areas. The PhD research project will be funded over this three year period and supervised with a team tailored to specific topics.
During the PhD, students will continue to build on their skills with specific training on Leadership, Innovation & Enterprise and Responsible Research and Innovation. Students will also be given the opportunity for funded secondments to provide further real-world understanding of the relevant of their research from an industry perspective.
Cohort based Learning and Research
The CDT encourages a culture of vertical and horizontal peer-to-peer engagement and co-working. The centre’s tightly-knit research community, made up of EPSRC and Industry funded students, engage in an integrated manner throughout the programme via cohort-based activities and challenges, they also work collaboratively with industry.
Cohort-based activities will focus on group working and industry interaction, around innovation and entrepreneurship. This will ensure that our researchers will deliver cutting edge solutions for economic prosperity across the geospatial industries and applied user sectors.
PhD Researcher Training and Development
While studying with the CDT, students will have access to training at Newcastle University and the University of Nottingham that broadly follows the Vitae Researcher Development Framework. Additionally, as the CDT is funded under the EPSRC CDT ‘Towards a Data Lead Future’ priority topic, students will also receive specific training on Responsible Research and Innovation and also Enterprise and Innovation, which will be delivered by experts in these areas.
Interdisciplinary Research Theme
Research students studying with the CDT will receive technical training around five core geospatial themes; spatial data capture and interpretation, statistical and mathematical methods, Big Data spatial analytics, spatial modelling and simulation, and visualisation and decision support. In addition, building on existing internationally leading interdisciplinary research, together with leading research centres, we will develop interdisciplinary PhD research projects jointly supervised between the geospatial expertise of the CDT and the applied domain experts (see Research Themes).
Working with Industry Partners and Government
Our programme and interdisciplinary research themes have been informed through consultation with over 40 CDT industry partners. Our Partnerships with the global geospatial industry, applied user base, professional bodies, and the public sector will play an important role in ensuring the transformational capability of the CDT to deliver the next generation of geospatial engineers, scientists and practitioners. While studying with the CDT, students will have continued access to our industry network, as well as the opportunity to undertake work placements and conduct collaborative research.
