Postgraduate Research Course

PhD Data Science

PhD Data Science

Overview

The details
Data Science
October 2025
Full-time
4 - 5 years
Colchester Campus

An Integrated PhD provides a route into research study if you do not have a Masters degree, or have very little research training. It enables you to spend your first year completing a Masters-level qualification, followed by a full-time PhD studied over 3-4 years. We also offer a ‘standard' PhD in this subject which can be studied either full-time (3-4 years) or part-time (6-7 years).

The techniques we use to model and manipulate data guide the political, financial and social decisions that shape our modern society and are the basis of growth of the economy and success of businesses. Technology is growing and evolving at an incredible speed, and both the rate of growth of data we generate and the devices we use to process it can only increase.

Data science is a growing and important field of study with a fast-growing number of jobs and opportunities within the private and public sector. The application of theory and methods to real-world problems and applications is at the core of data science, which aims especially to use and to exploit big data.

If you are interested in solving real-world problems, you like to develop skills to use smart devices efficiently, you want to use and to foster your understanding of mathematics, and you are interested and keen to use statistical techniques and methods to interpret data, then the first year of our Integrated PhD Data Science may be for you.

In your second year you move onto the PhD element of the course. We have staff members available to act as supervisors across a number of areas within data science. Possible areas of research include: artificial intelligence, classification/supervised learning, clustering/unsupervised learning, data science education, deep learning, industry 4.0, information retrieval, mathematical foundations of data science, multidimensional scaling, optimisation, and statistical learning.

The University of Essex is a leading institution worldwide on Data Science Education. We have a strong track record on Knowledge Transfer Partnerships (KTP) with data-driven industries, for example: Profusion, Mondaq, MSXI and Ocado. We have two research groups: Data Science and Mathematics.

All University of Essex research students have access to our innovative and unique scheme, Proficio. Postgraduate research students are automatically enrolled on Proficio, which provides a variety of training courses, and a fund of up to £2,500 per student for conference attendance and relevant external training courses.

Why we're great.
  • We are committed to developing the data scientists of the future.
  • We have active links with industry to broaden your employment potential and placement opportunities.
  • Our data science courses benefit from the Institute of Analytics and Data Science (IADS), the Institute of Social and Economic Research (ISER) and the UK Data Archive, all based at the University of Essex.

Our expert staff

Today's computer scientists are creative people who are focused and committed, yet restless and experimental. We are home to many of the world's top scientists, and our staff are driven by creativity and imagination as well as technical excellence. Specialist staff working on data science and analytics include:

  • Dr Luca Citi – machine learning, learning from biological signals and data (EEG, etc)
  • Professor Maria Fasli – machine learning, adaptation, semantic information extraction, ontologies, data exploration, recommendation technologies
  • Professor Berthold Lausen – biostatistics, classification and clustering, data science education, event time data, machine learning, predictive modelling
  • Professor Abdel Salhi – data mining, numerical analysis, optimisation
  • Professor Spyros Vrontos – actuarial mathematics and actuarial modelling
  • Professor Xinan Yang – approximate dynamic programming, Markov decision process

Our School of Mathematics, Statistics and Actuarial Science has an international reputation in all areas of mathematical sciences including; statistical learning, artificial intelligence, classification/supervised learning, clustering/unsupervised learning, data science education, actuarial science, mathematical statistics, operational research, applied mathematics, pure mathematics, and mathematics education.

We encourage PhD students to meet with their supervisor regularly. While undertaking your research within our School, joint supervision across other Essex departments and schools is possible.

Your PhD should lead to publications in academic journals. Our PhD students have had papers accepted and published in journals such as: Advances in Data Analysis and Classification; BMC Bioinformatics; Ecology; Journal of Physics A: Mathematical and Theoretical; Mathematical Modelling of Natural Phenomena; and The North American Journal of Economics and Finance.

Specialist facilities

  • Our School of Mathematics, Statistics and Actuarial Science is based in the University's state-of-the-art STEM Centre
  • All computers run either Windows 10 or are dual boot with Linux
  • Software includes Java, Prolog, C++, Perl, Mysql, Matlab, DB2, Microsoft Office, Visual Studio, and Project
  • You have access to CAD tools and simulators for chip design (Xilinx) and computer networks (OPNET)
  • We also have specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors
  • Collaborate with the Essex Institute of Data Analytics and Data Science (IADS) and the ESRC Business and Local Government (BLoG) Data Research Centre of the University of Essex
  • The UK Data Archive and the Institute for Social and Economic Research (ISER) at Essex contribute to our internationally outstanding data science environment

Your future

With a predicted shortage of data scientists, now is the time to future-proof your career. Data scientists are required in every sector, carrying out statistical analysis or mining data on social media, so our course opens the door to almost any industry, from health, to government, to publishing.

Our graduates are highly sought after by a range of employers and find employment in financial services, scientific computation, decision making support and government, risk assessment, statistics, education and other areas. Our recent graduates have gone onto work as data scientists and data analysts in both the private and public sectors.

Many of our former PhD students have gone on to work as academics in prominent institutions across the world, such as the University of Bristol, University of Cambridge, University of Nottingham and many other international universities. Some have also remained at the University of Essex, working as postdoctoral research fellows, research impact officers, or lecturers.

Other graduates have joined organisations like the Met Office, the Ministry of Defence, and companies based in the City of London. There is a high demand for data science experts in all sectors of the economy, so our graduates are sought after in the UK and abroad.

We additionally work with our Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

“The journey of a PhD student is just like a roller coaster, so make sure you take the time to celebrate the wins and reflect on the losses. My PhD involves examining the process of skeletal muscle activation/deactivation by developing novel mathematical methods to extract dynamic information from image data. The most enjoyable aspect of my work is the flexibility it gives me as an individual and being able to deepen my understanding in the field of Bayesian statistics, which I find particularly interesting. In the future I plan to work in the industry as a Data Scientist, on various projects related either to macroeconomics or finance.”

Madalina Mihailescu, PhD Data Science student

Entry requirements

UK entry requirements

A good honours degree in one of the following subjects: Mathematics, Actuarial Science, Statistics, Operational Research, Computer Science, Finance, Economics, Business Engineering.

Our four year integrated PhD, allows you to spend your first year studying at Masters level in order to develop the necessary knowledge and skills and to start your independent research in year two.

International & EU entry requirements

We accept a wide range of qualifications from applicants studying in the EU and other countries. Get in touch with any questions you may have about the qualifications we accept. Remember to tell us about the qualifications you have already completed or are currently taking.

Sorry, the entry requirements for the country that you have selected are not available here. Please contact our Graduate Admissions team at pgquery@essex.ac.uk to request the entry requirements for this country.

English language requirements

If English is not your first language , we require IELTS 6.0, or equivalent with a minimum of 5.5 in all other components.

Structure

Course structure

Most of our taught courses combine compulsory and optional modules, giving you freedom to pursue your own interests. All of the modules listed below provide an example of what is on offer from the current academic year. Our Programme Specification provides further details of the course structure for the current academic year.

Our research-led teaching is continually evolving to address the latest challenges and breakthroughs in the field. The course content is therefore reviewed on an annual basis to ensure our courses remain up-to-date so modules listed are subject to change.

The research element of your degree doesn't have a taught structure, giving you the chance to investigate your chosen topic in real depth and reach a profound understanding. In communicating that understanding, through a thesis or other means, you have a rare opportunity to generate knowledge. A research degree allows you to develop new high-level skills, enhance your professional development and build new networks. It can open doors to many careers.

We understand that deciding where and what to study is a very important decision for you. We'll make all reasonable efforts to provide you with the courses, services and facilities as described on our website and in line with your contract with us. However, if we need to make material changes, for example due to significant disruption, we'll let our applicants and students know as soon as possible.

Components and modules explained

Components

Components are the blocks of study that make up your course. A component may have a set module which you must study, or a number of modules from which you can choose.

Each component has a status and carries a certain number of credits towards your qualification.

Status What this means
Core
You must take the set module for this component and you must pass. No failure can be permitted.
Core with Options
You can choose which module to study from the available options for this component but you must pass. No failure can be permitted.
Compulsory
You must take the set module for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.
Compulsory with Options
You can choose which module to study from the available options for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.
Optional
You can choose which module to study from the available options for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.

The modules that are available for you to choose for each component will depend on several factors, including which modules you have chosen for other components, which modules you have completed in previous years of your course, and which term the module is taught in.

Modules

Modules are the individual units of study for your course. Each module has its own set of learning outcomes and assessment criteria and also carries a certain number of credits.

In most cases you will study one module per component, but in some cases you may need to study more than one module. For example, a 30-credit component may comprise of either one 30-credit module, or two 15-credit modules, depending on the options available.

Modules may be taught at different times of the year and by a different department or school to the one your course is primarily based in. You can find this information from the module code. For example, the module code HR100-4-FY means:

HR 100  4  FY

The department or school the module will be taught by.

In this example, the module would be taught by the Department of History.

The module number. 

The UK academic level of the module.

A standard undergraduate course will comprise of level 4, 5 and 6 modules - increasing as you progress through the course.

A standard postgraduate taught course will comprise of level 7 modules.

A postgraduate research degree is a level 8 qualification.

The term the module will be taught in.

  • AU: Autumn term
  • SP: Spring term
  • SU: Summer term
  • FY: Full year 
  • AP: Autumn and Spring terms
  • PS: Spring and Summer terms
  • AS: Autumn and Summer terms

COMPONENT 01: COMPULSORY

Mathematics - Research
(0 CREDITS)

This module is for PhD students who are completing the research portions of their theses.

View Mathematics - Research on our Module Directory

COMPONENT 01: OPTIONAL

Option(s) from List A
(30 CREDITS)

COMPONENT 02: OPTIONAL

Option(s) from List B
(30 CREDITS)

COMPONENT 03: COMPULSORY

Applied Regression and Experimental Data Analysis
(15 CREDITS)

This module is concerned with the application of regression models to the analysis of data. The underlying assumptions will be discussed and general results are obtained using matrices. You will be introduced to the standard approach to the analysis of normally distributed data using ANOVA, as well as the methods for the design and analysis of efficient experiments. The general methodology is extended to nonlinear regression, generalised regression and the analysis of multidimensional contingency tables.

View Applied Regression and Experimental Data Analysis on our Module Directory

COMPONENT 04: COMPULSORY

Applied Statistics
(15 CREDITS)

In this module, you will study three application areas of statistics - multivariate methods, demography and epidemiology, and sampling, and how to apply and assess these methods in a variety of situations.

View Applied Statistics on our Module Directory

COMPONENT 05: COMPULSORY

Machine Learning
(15 CREDITS)

Humans can often perform a task extremely well (e.g., telling cats from dogs) but are unable to understand and describe the decision process followed. Without this explicit knowledge, we cannot write computer programs that can be used by machines to perform the same task. “Machine learning” is the study and application of methods to learn such algorithms automatically from sets of examples, just like babies can learn to tell cats from dogs simply by being shown examples of dogs and cats by their parents. Machine learning has proven particularly suited to cases such as optical character recognition, dictation software, language translators, fraud detection in financial transactions, and many others.

View Machine Learning on our Module Directory

COMPONENT 06: COMPULSORY

Data Visualisation
(15 CREDITS)

In a world increasingly driven by data, the need for analysis and visualisation is more important than ever. In this module you will look at data through the eyes of a numerical detective. You will work on the lost art of exploratory data analysis, reviewing appropriate methods for data summaries with the aim to summarise, understand, extract hidden patterns and identify relationships. You will then work on graphical data analysis, using simple graphs to understand the data, but also advanced complex methods to scrutinise data and interactive plots to communicate data information to a wider audience. For data analysis and visualisations you will use R-studio, and a combination of R-shiny applications and google visualisations for interactive plotting.

View Data Visualisation on our Module Directory

COMPONENT 07: COMPULSORY

Research Skills and Employability
(0 CREDITS)

What skills do you need to succeed during your studies? What about after university? How will you harness your knowledge and soft skills to realise your career goals? This module helps you take an active role in developing transferrable skills and capitalising on your unique background. As well as broad reflection on your professional development, this module will help you explore different career directions and prepare you for the application process, supported by an advisor from within the department.

View Research Skills and Employability on our Module Directory

COMPONENT 08: CORE WITH OPTIONS

MA981-7-FY or MA983-7-SU
(60 CREDITS)

Teaching

  • Core components can be combined with optional modules, to enable you to gain either in-depth specialisation or a breadth of understanding
  • Learn to use LATEX to produce a document as close as possible to what professional mathematicians produce in terms of organisation, layout and type-setting
  • Our postgraduates are encouraged to attend conferences and seminars

Assessment

  • Our taught modules are assessed on the results of your written examinations, together with continual assessments of your practical work and coursework

Dissertation

A PhD (with a minimum period of three years) typically involves wide reading round the subject area in your first year, then gradually developing original results over your second and third years, before writing them up in a coherent fashion. The resulting thesis is expected to make a significant contribution to knowledge.

Your PhD is awarded after your successful defence of your thesis in an oral examination (viva), in which you are interviewed about your research by two examiners, at least one of whom is from outside Essex.

Fees and funding

Home/UK fee

TBC

International fee

£19,650 per year

What's next

Open Days

We hold Open Days for all our applicants throughout the year. Our Colchester Campus events are a great way to find out more about studying at Essex, and give you the chance to:

  • tour our campus and accommodation
  • find out answers to your questions about our courses, graduate employability, student support and more
  • talk to our Fees and Funding team about scholarship opportunities
  • meet our students and staff

If the dates of our organised events aren’t suitable for you, feel free to get in touch by emailing tours@essex.ac.uk and we’ll arrange an individual campus tour for you.

Applying

You can apply for this postgraduate course online. Before you apply, please check our information about necessary documents that we'll ask you to provide as part of your application.

We encourage you to make a preliminary enquiry directly to a potential supervisor or the Graduate Administrator within your chosen Department or School. We encourage the consideration of a brief research proposal prior to the submission of a full application.

We aim to respond to applications within four weeks. If we are able to offer you a place, you will be contacted via email.

For information on our deadline to apply for this course, please see our ‘how to apply' information.

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At Essex we pride ourselves on being a welcoming and inclusive student community. We offer a wide range of support to individuals and groups of student members who may have specific requirements, interests or responsibilities.

Find out more

The University makes every effort to ensure that this information on its programme specification is accurate and up-to-date. Exceptionally it can be necessary to make changes, for example to courses, facilities or fees. Examples of such reasons might include, but are not limited to: strikes, other industrial action, staff illness, severe weather, fire, civil commotion, riot, invasion, terrorist attack or threat of terrorist attack (whether declared or not), natural disaster, restrictions imposed by government or public authorities, epidemic or pandemic disease, failure of public utilities or transport systems or the withdrawal/reduction of funding. Changes to courses may for example consist of variations to the content and method of delivery of programmes, courses and other services, to discontinue programmes, courses and other services and to merge or combine programmes or courses. The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications. The University would inform and engage with you if your course was to be discontinued, and would provide you with options, where appropriate, in line with our Compensation and Refund Policy.

The full Procedures, Rules and Regulations of the University governing how it operates are set out in the Charter, Statutes and Ordinances and in the University Regulations, Policy and Procedures.

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