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Computer Science and Informatics (MSc by Research)

2024-25 (also available for 2023-24)

This course is eligible for Master's loan funding. Find out more.

Start date

2 October 2023

15 January 2024

16 April 2024

Duration

The maximum duration for an MSc by Research is 1 year (12 months) full-time or 2 years (24 months) part-time with an optional submission pending (writing-up) period of 4 months.

Sometimes it may be possible to mix periods of both full-time and part-time study.

If studying on a part-time basis, you must establish close links with the University and spend normally not less than an average of 10 working days per year in the university, excluding participation in activities associated with enrolment, re-registration and progression monitoring. You are also expected to dedicate 17.5 hours per week to the research.

Application deadlines

About the research degree

A Master of Science (MSc) by Research allows you to undertake a one-year (full-time) research degree. It contains little or no formal taught component. This type of study gives you the chance to explore a research topic over a shorter time than a more in-depth doctoral programme.

Our research degrees are available as full-time, part-time and some are offered distance learning.

Research Master's students choose a specific project to work on and have a greater degree of independence in their work than is the case with a taught Master’s course.

You’ll be expected to work to an approved programme which you will develop in conjunction with your supervisor within the first few months of starting your studies. Whilst undertaking the research project you will also develop your research skills by taking part in training courses and events.

You will be appointed a main supervisor who will normally be part of a supervisory team, comprising up to three members. The research supervisor will advise and support you on your project.

At the end of the project, you write up your findings in the form of a short thesis of around 25,000 words, which will then be examined.

On successful completion, you will be awarded your degree and if you have enjoyed this taste of research, you may then decide to apply for the full research doctoral degree (PhD).

Entry requirements

The normal entry requirements for enrolment on a MSc by Research is an upper second honours degree (2.1) from a UK university or a qualification of an equivalent standard, in a discipline appropriate to that of the proposed programme to be followed.

If your first language is not English, you will need to meet the minimum requirements of an English Language qualification. The minimum for IELTS is 6.0 overall with no element lower than 5.5, or equivalent. Read more about the University’s entry requirements for students outside of the UK on our Where are you from information pages.

Why choose Huddersfield?


There are many reasons to choose the University of Huddersfield and here are just five of them:

  1. We were named University of the Year by Times Higher Education in 2013.
  2. Huddersfield is the only University where 100% of permanent teaching staff are Fellows of the Higher Education Authority.
  3. Our courses have been accredited by 41 professional bodies.
  4. 94.6% of our postgraduate students go on to work and/or further study within six months of graduating.
  5. We have world-leading applied research groups in Biomedical Sciences, Engineering and Physical Sciences, Social Sciences and Arts and Humanities.

What can I research?

There are several research topics available for this degree. See below examples of research areas including an outline of the topics, the supervisor, funding information and eligibility criteria:

Outline

Conversational chatbots are a popular area of development. The aim of this project is to develop a conversational chatbot for explaining the collaborative decision making between human agents and automated planning agents. The chatbot will be capable of various dialogue types such as information-seeking, deliberation, and persuasion; in addition, the dialogue will be based on patterns of argument schemes and critical questions. This project will involve a detailed research study of the structure of argumentative dialogue with the aim of devising new and effective dialogue protocols and strategies. The successful candidate will be expected to focus on an application domain. The underlying techniques will be argumentation theory and dialogue, knowledge representation and reasoning, automated planning, and natural language processing.

Essential attributes for the candidate: • Knowledge of argumentation theory and dialogue. • Knowledge of knowledge representation and reasoning. • Knowledge of automated planning and scheduling. • Experience of fundamental Natural Language Processing (NLP). • Good written and communication skills. • Strong motivation, with evidence of independent research skills relevant to the project.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

How to apply

Outline

Argument mining is a research area within natural language processing. The aim of argument mining is the automatic identification and extraction of argumentative structure from real world textual resources such as legal documents, product reviews, online debates or newspaper articles. This project will involve a detailed research study of the structure of natural language arguments with the aim of devising new and effective computational argument mining techniques. The successful candidate will be expected to focus on an application domain and extend existing natural language or machine learning techniques applied to the argument mining domain.

Essential attributes for the candidate: • Experience of fundamental Natural Language Processing (NLP) or Machine Learning (ML) techniques. • Competent in applying NLP toolkits, such as NLTK or Spacy, or ML toolkits such as Scikit-Learn. • Knowledge of argumentation theory and defeasible reasoning would be advantageous. • Good written and communication skills. • Strong motivation, with evidence of independent research skills relevant to the project.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

How to apply

Outline

The aim of this project is to use natural language processing and information retrieval techniques to extract relevant information from medical notes. This will entail developing a thorough understanding of existing methods and tools, testing them on concrete collections of medical notes (e.g. in mental health) and developing novel methods improving on the state of the art. In some cases, medical texts will be semi-structured, thus making analysis easier, but in other cases text will be free, which poses the biggest challenge. Analysis work may have to be carried out in collaboration with medical experts who will assess the validity and usefulness of the extracted knowledge.

The successful candidate will have a thorough computer science education, and will have some specialized knowledge in artificial intelligence, natural language processing or information retrieval.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

How to apply

Outline

It is increasingly important that the skills gained within learning are clearly mapped to job roles and that they are communicated clearly to employers, governments and educational providers. Using a 21st Century Skills framework this research will explore a range of courses and job roles to categorise learning and to therefore support learning analytics approaches based on digital skills development.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

How to apply

Outline

With the increasing success of deep learning models and the huge availability of social media data, many exciting research problems are open for exploration. In the quest to make computers more amenable to natural language through useful computational tools, the proposed project will focus on developing an NLP pipeline with a wide range of applications in uncovering meanings in data, especially those expressed in human natural language (with emphasis on low resource languages). Among the objectives of the project is to support pedagogical activities in low resource languages.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

How to apply

Outline

Mental disorders and diseases affect a large proportion of the whole world population, including children, adolescents and elderly people, causing disabling and life-threatening conditions. They are cause for inequity, social stigma and discrimination, and human rights violations. Care services are limited, costly and often insufficient. In this context non-pharmacological interventions are increasingly important for health and social care. This project offers to students the opportunity to investigate uses of technology to enhance the design, implementation and evaluation of non-pharmacological interventions through addressing one of the following research lines: a) delaying onset and progression of disorders and diseases (e.g. through personalized and adaptive training of key psycho-physical capabilities); b) preserving general function and autonomy (e.g. through augmentation of cognitive, affective and behavioural capabilities, and technology-mediated, personalized activity monitoring and support); c) promoting engagement in daily life activities (e.g. through technology-mediated, personalised activity monitoring, adaptive support and stimulation of activity); d) enhancing rehabilitation (e.g. through personalized and adaptive monitoring and support of rehabilitation activities); e) enhancing social integration (e.g. through social networking technologies to facilitate meaningful social interactions remotely); f) enhancing the personalization, quality and efficiency of care provided by formal and informal caregivers (e.g. through facilitating the monitoring of sufferers’ conditions and activity, the provision of adaptive and personalized activity support, and remote interactions between sufferers and caregivers). To address these lines, students will investigate innovative approaches integrating complexity science, systemic design, human factors and ergonomics, and exploring novel uses of cutting-edge technologies including: assistive technologies; Internet of Things; autonomous agents; affective computing; deep learning; context-aware computing; biometric monitoring; activity tracking; augmented and virtual reality; digital games; social media. Projects will focus on high social impact mental disorders and diseases such as dementia, autism, attention deficit hyperactivity and brain injury.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

How to apply

Outline

Healthcare offers unique challenges for the deployment of machine learning models where the demands for interpretability and performance in general is much higher as compared to most other domains. Given that the cost of model misclassification is potentially high, explanations with respect to how a machine made conclusion is derived play a significant role informing clinicians making unbiased decisions. Knowledge-based systems aim to represent knowledge explicitly via tools such as if-then rules, which allow such a system to reason about how it reaches a conclusion and to provide explanation of its reasoning to end users. Fuzzy systems have been considered effective in building such rule-based systems with one of the most important advantages lying in their inherent interpretability as they support the explicit formulation of, and inference with, domain knowledge, gaining insights into the complex problems and facilitating the explanation of their solutions.

The aim of this PhD project is to develop fuzzy rule-based systems with a particular focus on scenarios of healthcare systems. At the initial phase, the project will look into a number of existing approaches proposed to address the interpretability issues of medical systems, as well as the recently established fuzzy rule-based models. A core part of the project will involve the design and implementation of a specific fuzzy rule-based model that will work with carefully selected healthcare aspects. The implemented system will be evaluated with respect to simulated bench mark data sets first, followed by a close examination of how such a system may perform in collaboration with medical doctors when applied to a diagnostic problem of realistic complexity.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

How to apply

Outline

Learning Analytics is an increasingly important area of research which has applications both within education and more broadly within organisations and society. In order to develop effective analytical algorithms it is important to better understand personalised learning. What makes a learning experience “personalised”, in the eye of the learner? To what extent and how can perception of personalisation be ascertained and monitored throughout the learning experience? What can we learn from games about all this? To address these questions, this study will investigate personalisation in learning and learning analytics in relation to this from a game-based perspective. Through a human factors and ergonomics approach, prototypical game systems and learning systems will be analysed and compared. Accordingly, mechanics that define personalisation of learning in both game-based and non-game contexts will be modelled. These mechanics will then be analysed to identify measurable indicators of personalisation of the learning experience. A learning analytics framework will finally be formulated based on the identified indicators, and tested through appropriate mixed methods approaches.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

How to apply

Outline

There is a necessity to consider aspects of security when designing software applications. A contributing factor is the increasing legal and financial pressures software developers are under should their software be left vulnerable. This is further exacerbated by the ease of performing large-scale automated software attacks. There are many best practice guides and standardised design patterns that can be followed to ensure a high-level of security is maintained, but such advice is often provided by a subject expert. This research aims to investigate whether learning what an adversary looks for to determine whether a system is vulnerable, as well as how they attack a software system, can be used to build-in simple deterrents that may ultimately increase security with very little software development effort. This project aims to leverage the fundamental philosophy from ‘secure-by-design’ research within crime prevention and construction sectors. It is foreseen that this project will require the input from cyber criminals to determine what they look for within a software system to determine if it is worth attacking. This will then inform a phase of research into establishing key recommendations to consider during software design to prevent the likelihood of being attacked. Case studies will then be performed to evaluate the developed approach.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

How to apply

Outline

The Internet of Things (IoT) is the vision of a network of physical objects (“things”) The Internet of Things (IoT) is the vision of a network of physical objects (“things”) equipped with sensors, software and networking capabilities which enable these objects to collect and exchange data. The PhD project would investigate approaches and develop novel methods for (a) enriching IoT data by linking them to ontologies and other data and information sources, and (b) providing reasoning services for processing IoT data at a high level of abstraction. Addressing (a) would be a major step towards achieving a Web of Things which would be siting on top of IoT functionalities (just like the WWW is residing on top of the Internet). Addressing (b) would enable the intelligent processing of huge amounts of IoT data, and requires to overcome major challenges in terms of the size and dynamicity of IoT data, among others. The project is suitable for a PhD student who has already acquired significant knowledge on semantic and knowledge technologies, e.g. in the areas of semantic web, linked data management, knowledge representation and reasoning, or logic programming. equipped with sensors, software and networking capabilities which enable these objects to collect and exchange data. The PhD project would investigate approaches and develop novel methods for (a) enriching IoT data by linking them to ontologies and other data and information sources, and (b) providing reasoning services for processing IoT data at a high level of abstraction. Addressing (a) would be a major step towards achieving a Web of Things which would be siting on top of IoT functionalities (just like the WWW is residing on top of the Internet). Addressing (b) would enable the intelligent processing of huge amounts of IoT data, and requires to overcome major challenges in terms of the size and dynamicity of IoT data, among others. The project is suitable for a PhD student who has already acquired significant knowledge on semantic and knowledge technologies, e.g. in the areas of semantic web, linked data management, knowledge representation and reasoning, or logic programming.

Funding

Please see our Research Scholarships page to find out about funding or studentship options available.

Deadline

Our standard University deadlines apply. Please see our Deadlines for Applications page to find out more.

Supervisors

How to apply

Computing has a vibrant and rapidly growing research community with expertise in diverse areas, for example visualisation, information and systems engineering, and intelligent systems.

Our aim is to research and develop new methods and technology in computer science that will have a real impact on global grand challenges in areas such as transport, health, security and energy.

There is a wide range of topics which can be researched, including the following research areas:

  • Artificial intelligence: planning, autonomous systems, knowledge representation and reasoning
  • Information systems: Web-based information systems, semantic web, big data
  • Human-Computer Interaction: visualisation, computer games

In the past, research has been conducted in collaboration with prestigious national and international partners from academia (e.g. Oxford, UCL, Bristol, Newcastle, Stanford, Bologna, VU Amsterdam, Vienna) and industry (e.g. British Telecom, IBM, Schlumberger).

To find out more about the research we conduct, take a look at our Research, Innovation and Skills webpages, where you will find information on each research area. To find out about our staff visit ‘Our experts’ which features profiles of all our academic staff.

Student support

At the University of Huddersfield, you'll find support networks and services to help you get ahead in your studies and social life. Whether you study at undergraduate or postgraduate level, you'll soon discover that you're never far away from our dedicated staff and resources to help you to navigate through your personal student journey. Find out more about all our support services.

Researcher Environment

Our postgraduate researchers contribute to our thriving research culture at Huddersfield, in return we provide an experience that enhances your potential and inspires you to think big and become a globally competitive researcher.

Join our community of like-minded people who are passionate for research and gain access to world-leading facilities, advanced research skills training, and expert careers advice.

Reduced inequalities

We recently ranked 6 out of 796 global institutions for reduced inequalities in the Times Higher Impact ratings – this recognises our research on social inequalities, policies on discrimination and commitment to recruit staff and students from underrepresented groups (THE Impact Rankings 2022).

World-leading

We are in the top 50 UK universities for research power, and nearly two thirds of our research environment is classified as world leading and internationally excellent (REF2021).

As a researcher, you’ll gain access to our Researcher Skills Development Programme through the Graduate School, to help broaden your knowledge and access tools and skills to improve your employability. The programme is mapped against Vitae’s Researcher Development Framework (RDF), you’ll benefit from Vitae’s career support as well as our own programme. We also have a team dedicated to improving the academic English needed for research by our international PGRs. Our training is delivered in a variety of ways to take advantage of online platforms as well as face-to-face workshops and courses. You can access a range of bespoke training opportunities and in-person events that are tailored to each stage of your journey, including: * sessions on PhD thesis writing, publications and journals, post-doctoral opportunities, poster and conference presentations, networking, and international travel opportunities * opportunity to work and study abroad via the Turing Scheme through The Graduate School * externally accredited training programme with Advance HE (HEA) and CMI * online research training support accessed through a dedicated researcher module in Brightspace, the University’s Virtual Learning Environment * We also hold a series of PGR focussed events such as 3 Minute Thesis * PGR led research conference * informal events throughout the year.

Important information

We will always try to deliver your course as described on this web page. However, sometimes we may have to make changes as set out below.

When you are offered a place on a research degree, your offer will include confirmation of your supervisory team, and the topic you will be researching.

Whilst the University will use reasonable efforts to ensure your supervisory team remains the same, sometimes it may be necessary to make changes to your team for reasons outside the University’s control, for example if your supervisor leaves the University, or suffers from long term illness. Where this is the case, we will discuss these difficulties with you and seek to either put in place a new supervisory team, or help you to transfer to another research facility, in accordance with our Student Protection Plan.

Changes may also be necessary because of circumstances outside our reasonable control, for example the University being unable to access its buildings due to fire, flood or pandemic, or the University no longer being able to provide specialist equipment. Where this is the case, we will discuss these issues with you and agree any necessary changes.

Your research project is likely to evolve as you work on it and these minor changes are a natural and expected part of your study. However, we may need to make more significant changes to your topic of research during the course of your studies, either because your area of interest has changed, or because for reasons outside the University’s control we can no longer support your research. If this is the case, we will discuss any changes in topic with you and agree these in writing. If you are an international student, changing topics may affect your visa or ATAS clearance and if this is the case we will discuss this with you before any changes are agreed.

When you enrol as a student of the University, your study and time with us will be governed by the University’s Terms and Conditions and a framework of regulations, policies and procedures, which form the basis of your agreement with us. It is important that you familiarise yourself with these as you will be asked to agree to abide by them when you join us as a student. You will find a guide to the key terms here, along with the Student Protection Plan, where you will also find links to the full text of each of the regulations, policies and procedures referred to.

The Office for Students (OfS) is the principal regulator for the University.