Students at Lancaster University

PhD & Postgraduate Research

The department offers the opportunity to study for a research degree in any of the areas of interest of our staff members.

We offer the following PhD programs in the department:

You can find details of our research areas on our research pages, and we welcome direct contact to discuss possible projects. Lancaster is also home to the Statistics and Operational Research Centre (STOR-i) and is a participant in the North West Social Science Doctoral Training Partnership.

Students have a formal weekly meeting with their supervisor, but we usually supplement this with more frequent, informal contact. We will cover any skills gaps through additional lecture programmes or directed reading. You will have the opportunity to attend graduate lectures on topics of current research interest. You will also be able to participate in national schemes such as APTS, MAGIC and NATCOR and take part in internal seminars for students and staff. These are an ideal opportunity to gain valuable experience of communicating ideas to an audience while also receiving feedback, which can help set future research directions.

All PhD students have a departmental laptop of their own and encourage you to attend and present work at national and international conferences. Each new PhD student is also assigned an individual peer mentor. Your mentor will be a current senior PhD student, who you can approach for guidance regarding university-related concerns that you may encounter during the first year.

How to Apply

The application process is explained step-by-step here. Please click the headings to move to the next topic.

The first step if you are interested in studying for postgraduate research is to contact the PhD admissions tutor, Dr Juhyun Park, telling us which areas of mathematics or statistics you might be interested in researching. We will put you in touch with potential supervisors, help you to efficiently navigate the applications systems and the funding opportunities.

Application Process

  1. Contact the appropriate PhD admissions tutor for an initial discussion.
  2. Begin the online application process.
  3. After an initial screening, we will invite UK based applicants to visit the department to meet potential supervisors. (We provide support for standard travel costs.) For overseas-based applicants we will offer a Skype meeting.
  4. Following steps 2 and 3, you might be offered possible PhD projects/supervisors to choose from.
  5. If you do not require financial support from the University, you will quickly be informed of our decision. Otherwise, your application will be considered on a competitive basis with others; you will be informed of the decision after the application deadline (31 January).
  6. Completion of visa requirements for overseas candidates.
  7. Arrive in Lancaster to start your PhD.

The most important considerations when choosing to study for a PhD or MPhil are the project and supervisor. For this reason, we invite all UK based applicants to discuss research projects with potential supervisors. Whilst we welcome proposals for research projects from applicants, most research projects are developed by academics taking into consideration applicants’ strengths and knowledge.

At the bottom of this page, you can see a sample of possible projects offered by our staff, but please note that this list is only indicative and is not exhaustive. You should contact members of staff directly for more details. You might also wish to look at our research pages, to learn more about our specialisms.

All applicants for postgraduate study in the Department of Mathematics and Statistics need to complete an online application via the University Postgraduate Admissions Portal.

Once you have created an account at our Postgraduate Admissions Portal you will be able to fill in your personal details, background and upload supporting documentation.

Current Lancaster Students

If you are a current Lancaster student, or you have recently graduated from Lancaster, we can reduce the amount of information that you will need to provide as part of your application. You will need to provide only one reference and will not need to supply your Lancaster degree transcript.

You will need

  • Postgraduate application form, available once you have created an account in the online portal and selected your mode of study.
  • Two references – you should include at least one academic referee who can comment on your academic quality, performance and potential to pursue independent research.
  • Transcripts of previous higher education degrees or other courses that you have completed or for which you are currently studying. Please note, for transcripts in languages other than English, a certified English translation will be required.
  • A detailed CV (up to 3 pages) – this should cover academic achievements, past projects and any employment history.
  • Personal statement (up to 2 pages) – you should include information on your research interests, relevant experiences and the subject area that you would like to work in, and if possible, the name of the supervisor(s) you would like to work with.
  • If English is not your first language, proof of English language competency is required.
    • IELTS is the recommended test but we consider tests from other providers; please refer to the university's information on language requirements. If you have any concerns or questions, please contact the Faculty Postgraduate Admissions team for clarification.
    • Our requirements for IELTS are an overall score of at least 6.5, with no individual element below 6.0. If your score is below our requirements but all individual elements are at least 5.5, we may consider you for one of our pre-sessional English language programmes.

Please note that the Department does not require applicants to submit a research proposal. This is optional, but if an applicant would like further guidance on this issue, please contact the relevant PhD admissions tutor with the subject line your intended programme (e.g. PhD Mathematics or PhD Statistics etc.).

  • Entry date: our academic year starts in October and most students enter at this time. Entry in January or April is also possible. Applications are considered throughout the year.
  • Timeline: Applications are normally considered between October and May of the following year.
  • Categories of candidates: Different studentships have different eligibility criteria but broadly cover 3 categories: UK students, UK/EU students and Overseas (non-EU) students. All eligible applicants are automatically considered for available studentships.
  • Studentships deadline: Due to high demand for studentships we have a deadline of 31st January. All applications received by this date will receive equal consideration. Applications received after this deadline will be considered for any remaining studentships.
    Final studentships decisions are usually made by April but please feel free to contact us to find out whether studentships are still available.

There are additional special funding routes available in Statistics which have their own deadlines. Please visit the websites of the STOR-i Centre for Doctoral Training and North West Social Science Doctoral Training Partnership for more information.

Research Areas

Ranked joint 5th in the 2014 Research Excellence Framework (REF), Lancaster is one of the UK's top departments for research in mathematics and statistics.

Current Funding Opportunities

Details of any currently advertised funded PhD studentships are given below. You are strongly encouraged to contact the prospective supervisor before making an application.

Note that the majority of funding opportunities for October entry in any given year close before March of that year.  


  • Department PhD Studentships in Mathematics and Statistics in 2019/20


    The Department of Mathematics and Statistics at Lancaster University is inviting applications for fully-funded PhD positions in either Pure Mathematics or Statistics for the entry in October 2020.  Please see the PhD in Mathematics and PhD in Statistics course pages for details.

    Research projects

    Any research areas in Pure Mathematics or Statistics that are consistent with those of our staff members are considered and some examples of research topics and potential supervisors are available.

    Entry Requirements

    Applicants are expected to have a minimum of an upper-second class honours degree, or its equivalent, in Mathematics, Statistics or related fields. Preferably applicants will, or are expected to, hold a first class degree in MSci/MMath for Mathematics, MSc in Statistics/Data Science, though exceptional BSc students will also be considered.

    Funding eligibility

    The studentship normally covers full payment of tuition fees at UK/EU level plus a stipend for living expenses. All applicants from UK/EU/Overseas may apply. The funding is offered for 3.5 years of study for UK/EU candidates and 3 years of study for Overseas candidates.

    Application process

    The deadline for submitting applications for this studentship is 31 January 2020.  The guidelines on the application process are found in the How to Apply section. Note that all eligible candidates from the standard PhD applications are automatically considered.


    Those interested are encouraged to contact the PhD Admissions Officer, Dr J. Park ( Please provide your CV and transcripts.

  • PhD studentship on the Data Science for the Natural Environment (DSNE) project (UK/EU applicants)

    Applications are invited for a fully-funded PhD studentship in which you will learn to develop cutting-edge data science approaches to address a key environmental science challenge related to sustainable land use.

    The studentship is part of the £2.6 million EPSRC-funded grant Data Science for the Natural Environment (DSNE), a joint project between Lancaster University and the UK Centre for Ecology & Hydrology. This is an exciting opportunity to work at the heart of a multi-disciplinary team of researchers consisting of environmental scientists, computer scientists, statisticians and stakeholder organisations, working together to deliver methodological innovation in data science to tackle grand challenges around environmental change. The student will be registered at Lancaster University. The studentship covers the full fees and stipend of UK/EU applicants only (i.e. does not include the total fees of non-EU applicants).

    The DSNE research programme is a prestigious and high profile research programme targeting a paradigm shift in the role of data in environmental science and leading to long-term impact in decision making. The research is arranged around methodological developments in three core methodological themes (integrated statistical modelling, machine learning and decision-making, and virtual lab development), interlocked with three challenge themes from the environmental sciences (ice sheet melt prediction, air quality modelling and land-use modelling) The PhD topic available is listed below.

    Prospective applicants are encouraged to contact Professor Pete Atkinson ( or Professor Paula Harrison (email: before making an application.

    To apply, please send a letter of application to by 5pm Wednesday 18th March. The letter should include:

    • An explanation and reasoning about why you want to be considered for the project
    • An explanation of why your skillset and previous education will allow you to be successful in this project (a transcript of your undergraduate or masters degree programme is likely to be helpful)

    Unfortunately, while we can cover the full fees and stipend for UK/EU applicants, the full fee of non-EU applicants cannot be covered.

    Closing date: Wednesday 18th March

    Expected interview date: Wednesday 1st April

    Project details

    Downscaling and cross-scale integration of land use data and models for building pathways towards sustainable food and land-use systems

    Supervisors: Pete Atkinson, Paula Harrison and Pete Henrys

    Food and land use systems are unsustainable in every part of the world. Today’s practices drive biodiversity, forest, and other ecosystem losses; cause water scarcity, and threaten the health of freshwater ecosystems through chemical and fertiliser run-off. From a climate change perspective, food systems and land use are crucial. They account for over a quarter of global greenhouse gas emissions, deforestation, and unprecedented biodiversity loss. However, better land- and water-use planning, strengthened governance, policy reform, technological innovation and investment could deliver around a third of the mitigation the world needs by 2030 and help achieve the Paris Agreement’s long-term goal of keeping the rise of average global temperatures to “well below 2°C”.

    Most countries lack tools for integrated land use planning that take account of the complex synergies and trade-offs between agriculture, water, land use, biodiversity, healthy diets, and greenhouse gas emissions. Integrated assessment models which couple together multiple sectoral models to simulate some of these interdependencies have been developed at the global and European levels. However, such models are generally applied at very coarse spatial resolutions, whereas land management decisions are taken at finer spatial scales. This PhD will develop methods for downscaling a global/European integrated assessment model to the UK. This could include integrating it with other land-use modelling approaches more appropriate to capturing fine resolution processes and interactions. It could also include testing new machine learning techniques that automatically refine or improve fine-resolution simulations based on new land-use data. The PhD will also contribute to the development of methods to interface the UK model with multiple country versions from different parts of the world as well as the global model. Crucially, this will enable international trade flows in agricultural and forest commodities to be integrated into national decision-making, ensuring the UK and other countries do not meet their national goals by exporting their environmental footprint. Scenario and pathway analysis will be undertaken with the interfaced multi-scale models to inform sustainable food and land-use systems in both national and international contexts accounting for the full propagation on uncertainty across model components and scales.

    The PhD will collaborate with the FABLE Consortium, which mobilises top knowledge institutions from G20 and other countries to support the development of the data and modelling infrastructure for long-term pathways towards sustainable food and land-use systems. Currently, 22 countries are involved in FABLE modelling activities covering 62% of the world’s population (including China, India, Brazil, Ethiopia, USA, Australia, Argentina and Indonesia). Hence, the PhD student will have the opportunity to interact with modellers and data scientists from these countries, as well as IIASA and the UN Sustainable Development Solutions Network (SDSN) who coordinate FABLE. This is also a unique opportunity to undertake a PhD with significant impact as outputs will help inform national policy debates in real-time as well as the intergovernmental processes on climate.

Self-Funded Opportunities

The Department also considered applications from self-funded students.   Please contact the relevant PhD admissions tutor (Mathematics - Professor Stephen Power; Statistics - Dr Juhyun Park) to discuss this possibility.

Studentships and Funding

As a postgraduate research student, you can be funded from several different sources:

  • Research Council Studentships: full payment of tuition fees plus a stipend for living expenses for UK applicants only. EU applicants may apply but normally only fees are paid.
  • EU-funded Studentships: normally full payment of tuition fees (at UK/EU level) plus a stipend for living expenses. No restrictions on applicants, unless specified, but overseas applicants would need to pay the difference in fees.
  • Department Studentships: normally full payment of tuition fees (at UK/EU level) plus a stipend for living expenses. No restrictions on applicants, unless specified, but overseas applicants would need to pay the difference in fees.
  • ESRC Studentship competition: The North West Social Science Doctoral Training Partnership (NWSSDTP) holds an annual competition for studentships, which can be used for study towards a PhD in Statistics or Social Statistics. The NWSSDTP is a collaboration between Lancaster, Manchester and Liverpool universities and offers an excellent range of PhD programme pathways and training courses for students who are part of this innovative scheme. Candidates may apply for funding towards masters and doctoral (1+3/2+2) study, or doctoral study only (+3/+2).
    Normally the competition for October entry takes place in January or February in the year of entry and requires a PhD proposal with a nominated supervisor. If you are interested, you are expected to contact the department before with an idea for a PhD proposal and find a supervisor who can work with you towards making an application.
  • Studentships funded by industry and other external sources: normally full payment of tuition fees (at UK/EU level) plus a stipend for living expenses. No restrictions on applicants, unless specified but overseas applicants would need to pay the difference in fees.
  • Self-funding: student responsible for tuition fees and living expenses. No restrictions on applicants.

PhD Supervisors

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