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Postgraduate Study

About the Department of Computer Science and Technology

The Department of Computer Science and Technology (known as the Computer Laboratory) is an academic department within the University of Cambridge that encompasses Computer Science, along with many aspects of Technology, Engineering and Mathematics.

The Department undertakes research in a broad range of subjects. It has an open and collaborative culture, supporting revolutionary fundamental computer science research, strong cross-cutting collaborations internally and externally, and ideas which transform computing outside the University. Current research areas include bioinformatics, computer architecture, computer vision, distributed systems, graphics and human-computer interaction, logic and semantics, machine learning, natural language processing, networking and wireless communication, operating systems and virtualization, programming, security, and sustainable computing.

2 courses offered in the Department of Computer Science and Technology

The aim of the course is to provide preparation appropriate for undertaking a PhD programme in computer science. Students take a mandatory course in research skills and select five taught modules from a wide range of advanced topics in computer science. Students also undertake a research project over two terms and submit a project report in early June. Research topic selection and planning occurs in the first term and the work is undertaken in subsequent terms. The taught modules are delivered in a range of styles. For example, there are traditional lecture courses, lecture courses with associated practical classes, reading clubs, and seminar-style modules.

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The Department of Computer Science and Technology undertakes research in a broad range of subjects within the disciplines of computer science, engineering, technology, and mathematics. Current research themes include Algorithms and ComplexityComputer ArchitectureGraphics, Vision and Imaging ScienceHuman-Centred Computing,  Machine Learning and Artificial IntelligenceMobile Systems, Robotics and AutomationNatural Language ProcessingProgramming Languages, Semantics and VerificationSecurity, and Systems and Networking

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3 courses also advertised in the Department of Computer Science and Technology

From the British Antarctic Survey

This PhD course takes place under the joint supervision of a research scientist at the British Antarctic Survey (BAS) and a University supervisor. Students may be based at BAS but will be registered for their degree with one of the partnering departments: Archaeology & Anthropology, Land Economy, Plant Sciences, Zoology, Earth Sciences, Geography and Scott Polar Research Institute, Applied Mathematics & Theoretical Physics, Chemistry, Engineering, Computer Science and Technology.

BAS welcomes enquiries from those interested in higher degrees in earth science subjects, physics, chemistry, mathematics, biology and related areas.

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From the Department of Earth Sciences

The UKRI Centre for Doctoral Training in the Application of Artificial Intelligence to the study of Environmental Risks (AI4ER) trains researchers (through several multidisciplinary cohorts) to be uniquely equipped to develop and apply leading-edge computational approaches to address critical global environmental challenges by exploiting vast, diverse and often currently untapped environmental data sets. Embedded in the outstanding research environments of the University of Cambridge and the British Antarctic Survey (BAS), the AI4ER CDT addresses problems that are relevant to building resilience to environmental hazards and managing environmental change. The primary application areas are:

  • Weather, Climate and Air Quality
  • Natural Hazards
  • Natural Resources (food, water & resource security and biodiversity)

Students in the CDT cohorts engage in a one-year MRes degree in Physical Sciences (Environmental Data Science) which includes a taught component and a major research element, followed by a three-year PhD research project. Students will receive high-quality training in research, professional, technical and transferable skills through a focused core programme with an emphasis on the development of data science skills through hackathons and team challenges. Training is guided by personalised advice and the expertise of a network of partners in industry, government, the third sector and beyond.

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From the Department of Chemistry

This cutting-edge Centre for Doctoral Training (CDT) in Automated Chemical Synthesis Enabled by Digital Molecular Technologies (SynTech) aims to develop a new generation of leaders in synthetic chemistry research with a focus on Machine Learning & Artificial Intelligence-driven techniques. 

Please note: The SynTech CDT programme is usually offered to full-time students due to the nature of the compulsory training during the first year, but applicants wishing to pursue part-time study are also welcome to apply. Part-time study will be considered on a case-by-case basis, so please discuss this option with the CDT-coordinator before making an application for this mode of study. The training programme and  associated timelines, for example the submission of reports, will be adjusted correspondingly.

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