| Program start date | Application deadline |
| 2023-09-01 | - |
Program Overview
Overview
This Integrated PhD in Computer Science provides an opportunity to make a unique contribution to computer science research. You'll work within a research group, guided by experts and supported by a team of advisers.
Our Computer Science Integrated PhD (IPhD) allows you to match your studies with your interests. You can choose from a wide range of modules and select your own focus for your final project.
Our computer science research
Based in the School of Computing, our research reflects our strengths, capabilities and critical mass. Research supervision is available under our seven research areas.
Advanced Model-Based Engineering and Reasoning (AMBER)
The AMBER group aims to equip systems and software engineering practitioners with effective methods and tools for developing the most demanding computer systems. We do this by means of models with well-founded semantics.
Open Lab
Open Lab is the leading academic research centre for human-computer interaction (HCI) and ubiquitous computing (Ubicomp) research outside of the USA. It conducts research across a wide range of fundamental topics in HCI and Ubicomp, including:
Interdisciplinary Computing and Complex BioSystems (ICOS)
ICOS carries out research at the interface of computing science and complex biological systems. We seek to create the next generation of algorithms that provide innovative solutions to problems arising in natural or synthetic systems. We use our interdisciplinary expertise in machine intelligence, complex systems and computational biology.
Scalable systems
The Scalable Systems group creates the enabling technology we need to deliver tomorrow's large-scale services. This includes work on:
Secure and Resilient Systems
The Secure and Resilient Systems group investigates fundamental concepts, development techniques, models, architectures and mechanisms that directly contribute to creating dependable and secure information systems, networks and infrastructures. We aim to target real-world challenges to the dependability and security of the next generation:
Educational Practice in Computing
The Educational Practice in Computing group focusses on encouraging, fostering and pursuing innovation in teaching computing science. Through this group, your research will focus on pedagogy. You'll apply your research to maximise the impact of innovative teaching practices, programmes and curricula in the School. Examples of innovation work within the group include:
Networked and Ubiquitous Systems Engineering (NUSE)
The NUSE group provides quality of life improvements in the digital age. They address challenges in systems engineering for real-world applications. This includes autonomous transportation, green energy, online safety, big data analysis and digital health.
Their core research strengths include:
Research excellence
The excellence of our research has been recognised through awards of large research grants. Three recent examples are:
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Important information
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Your course and study experience - disclaimers and terms and conditions
Please rest assured we make all reasonable efforts to provide you with the programmes, services and facilities described. However, it may be necessary to make changes due to significant disruption, for example in response to Covid-19.
View our Academic experience page, which gives information about your Newcastle University study experience for the academic year 2022-23.
See our terms and conditions and student complaints information, which gives details of circumstances that may lead to changes to programmes, modules or University services.
Program Outline
What you'll learn
The IPhD combines taught master's level modules with research. As an IPhD student, you'll initially study alongside students on one of our computer science master's. You can choose from one of the following:
Advanced Computer Science MSc
Bioinformatics MSc
Cloud Computing MSc
Computer Game Engineering MSc
Cyber Security MSc
Data Science MSc
Data Science (with Artificial Intelligence) MSc
Data Science (with Specialisation in Statistics) MSc
Data Science (with Visualisation) MSc
Human Computer Interaction MSc
Synthetic Biology MSc
Additionally you'll take the 30 credit short project module Project and Dissertation for MCOMP. The project topic should match the specialisation.
Modules
You will study modules on this course. A module is a unit of a course with its own approved aims and outcomes and assessment methods.
Course content changes
Module information is intended to provide an example of what you will study.
Our teaching is informed by research. Course content changes periodically to reflect developments in the discipline, the requirements of external bodies and partners, and student feedback.
Full details of the modules on offer will be published through the Programme Regulations and Specifications ahead of each academic year. This usually happens in May.
Optional modules availability
Some courses have optional modules. Student demand for optional modules may affect availability.
To find out more please see our terms and conditions.
