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.
3 courses offered in the Department of Computer Science and Technology
Advanced Computer Science - MPhil - Closed
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.
Computer Science - PhD
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 Complexity, Computer Architecture, Graphics, Vision and Imaging Science, Human-Centred Computing, Machine Learning and Artificial Intelligence, Mobile Systems, Robotics and Automation, Natural Language Processing, Programming Languages, Semantics and Verification, Security, and Systems and Networking.
Decision Making for Complex Systems UKRI AI CDT - PhD - Closed
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 Complexity, Computer Architecture, Graphics, Vision and Imaging Science, Human-Centred Computing, Machine Learning and Artificial Intelligence (ML and AI), Mobile Systems, Robotics and Automation, Natural Language Processing, Programming Languages, Semantics and Verification, Security, and Systems and Networking.
The UKRI AI CDT in Decision Making for Complex Systems is a programme offered in conjunction with the University of Manchester that aims to enable students to develop new fundamental AI capabilities in the context of a diversity of complex systems. Rather than working in isolation, as is usual in AI, the students will learn to develop these in a collaborative manner tied to a specific application domain. The CDT is focused on three areas, Uncertainty in complex systems, Decision-making with humans in the loop and Decision-making for ML systems. Model interpretability and explainability will be transversal to the three topics. Decision making with AI needs to be interpretable and explainable to facilitate interrogation of decision processes such that trust can be built by the human, and it is essential for understanding and meeting ethical and legal implications.
This CDT programme requires students to complete one year of training at the University of Manchester leading to award of a Postgraduate Diploma in Artificial Intelligence, followed by research for a PhD degree at either the University of Manchester or Cambridge. Applications for admission to the CDT programme are made to the University of Manchester in the first instance. Successful applicants who chose a research project at the University of Cambridge will be invited to apply for admission to this PhD. Further information about the course and how to submit an application can be found here https://www.cst.cam.ac.uk/admissions/phd.
Important: Applications to this PhD programme will only be considered from students who are registered on the UKRI AI CDT in Decision Making for Complex Systems at the University of Manchester.
2 courses also advertised in the Department of Computer Science and Technology
Antarctic Studies - PhD
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, Land Economy, Plant Sciences, Zoology, Earth Sciences, Geography and Scott Polar Research Institute, Applied Mathematics & Theoretical Physics, Chemistry, Engineering, Computer Science and Technology.
Biological Sciences - PhD - Closed
From the School of the Biological Sciences
The Cambridge Biosciences DTP is a four year fully-funded PhD programme that aims to create highly skilled and employable people. The programme offers training across 23 University Departments/Institutes and 3 Partner Institutes providing access to a wide range of research areas related to the strategic themes of the BBSRC. We offer three types of DTP studentships:
- DTP Standard
- Targeted
- iCase
During the programme, DTP Standard and Targeted students will undertake two ten-week rotations in different labs before commencing their PhD. They will receive training in a variety of areas including but not limited to statistics, programming, ethics, data analysis, scientific writing and public engagement. Students will also undertake a 12-week internship (PIPS).
iCase students are not required to undertake rotations but may do so if they feel that this training would be useful. They must undertake a placement with their Industrial Partner for a minimum of three months and a maximum of 18 months.
Students will be expected to submit their thesis at the end of the fourth year.
Part-time study, whilst not the norm, may be viable, depending on the project, and will be considered on a case by case basis so please discuss this option with your proposed supervisor before making an application for this mode of study.