statistics phd imperial

EPSRC CDT in Statistics and Machine Learning at Imperial College London and the University of Oxford

StatML admissions 2024/25:

• General applications are now closed. It is possible that at a future date funding will become available for additional specific projects, in such cases details will be provided here.

If you have any general questions, please contact Frédérique Godin at [email protected]

——————————— General applications are now closed! ————————————

Please refer to the institutions’ respective admission pages for guidelines and deadlines. We aim to award most of the studentships during this cycle. We may run a second round, if places are still available. 

If you have any general questions please contact Frederique Godin at [email protected]

We would like to receive applications from individuals who hold (or expect to receive) a masters level degree (or equivalent) in mathematics, statistics, physics, computer science, engineering, or in a closely related subject. 

Whilst the programme is normally intended for full-time study, we welcome applications for part-time study, including from those with established careers or caring responsibilities.

The majority of our funded studentships are limited to Home / Republic of Ireland nationals.  However, in recognition of the outstanding talent of many overseas students, both Oxford and Imperial offer several highly prestigious international scholarships designed to attract and reward the best students.

An additional source of funding open to all applicants, including overseas students through Imperial   College is via the “President’s scholarship”

To be considered for this scholarship, you need to follow the procedures on the Imperial website ( please note this differs to the standard CDT application procedure and there are specific deadlines unrelated to the CDT you need to adhere t o).  Furthermore, prior to applying, candidates must have contacted a supervisor in an academic department at Imperial College London who has agreed to supervise their research project and their name needs to be put on the application form.

In order to be considered for most Oxford University  scholarships, students must have applied by the 19th of January 2024.  

Please find listed information on eligibility, fee status and stipends:

For any information regarding the programme and admissions, please get in touch with Frédérique Godin at [email protected].

StatML Directors will be hosting online Q&A’s to provide information about the application process in 2024. The last one will be held by Prof Sarah Filippi on Wednesday January 10th, at 14.30.

To register your interest in joining the last session, please send an email to  Frédérique Godin at the above-mentioned email address. 

You can also get in touch with one of our Directors by writing to the email addresses below: 

• Professor Judith Rousseau  at  [email protected] , (Oxford) or 
• Dr Ed Cohen or Dr Sarah Filippi at [email protected]   (Imperial). 

Every student will have a home institution (either Imperial or Oxford) and will receive their degree from this institution. Training will take place at both institutions.    

During the admissions process, it will be determined which university (Imperial or Oxford) would be your home institution. You would have to fulfil the language requirements of your home institution. Links to the requirements: Imperial ,  Oxford .

• Please note that you will be required to provide supporting documents such as a personal statement/statement of purpose, your most recent transcript, your resume, and your references . You are not expected to write a research proposal, only a personal statement/statement of purpose, and your references should be received by the application deadline, or shortly after at most. 
• Your motivation for wanting to do a PhD
• Your motivation for choosing to apply to StatML 
• Explanation of which domains or questions in statistics and machine learning interest you the most and why. You may want to include any links between theses research interests and those of StatML supervisors.
• Anything we need to know to better understand you CV/transcript/references (e.g. if you had mitigating circumstances, let us know, but we do not need to know the details of the circumstances).
• Assessment and interviews will take place once applications have been received through the suggested university.
• Offers will be made by Imperial or by Oxford (depending on where you have applied to).

Should you have any further queries regarding the application process please do not hesitate to contact us.

Hear from our students

Find out more about the previous programme in the videos below. 

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Thank you, your report has been submitted. We will deal with the issue as soon as possible. If you have any other questions, please send an email to [email protected] .

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1 in 4 undergraduate applicants received an offer in 2021/22.

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1 in 4 postgraduate taught applicants received an offer in 2021/22.

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Least Competitive  

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Data sources

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The acceptance rate , or offer rate, represents the fraction of applicants who received an offer. Note that this will be generally lower the acceptances rates (acceptances divided by applicants) published by many other sources. This article explains it in more detail. The acceptances generally indicate the number of offer holders who accepted the offer and fulfilled its conditions. For some universities, however, it denotes the number of applicants who accepted the offer, regardless of whether they subsequently met its conditions.

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Department of Mathematics

Msc statistics.

Discover a diverse range of statistical tools, applications and methods.

Key information

Applications are now closed

Statistical ideas, tools and methods are used in almost all employment sectors, including banking and finance, government, medical research, the pharmaceutical industry and internet companies.

This one-year, full-time programme provides outstanding training in both theoretical and applied statistics. The variety of elective modules to choose from, allows you to develop your specialist interests, providing depth and exposure to a diverse range of statistical applications and methods.

We offer six streams on our MSc in Statistics programme:

• MSc Statistics (General)
• MSc Statistics (Applied Statistics)
• MSc Statistics (Biostatistics)
• MSc Statistics (Data Science)
• MSc Statistics (Statistical Finance)
• MSc Statistics (Theory and Methods)

The formal qualification received will include the name of the specialist stream and therefore can be used to indicate to employers or future research supervisors what they have specialised in during their MSc. For example: MSc Statistics (Applied Statistics).

A limited number of places exist for each specialist stream. If you are unsuccessful in applying for one of these, you will automatically be considered for the general stream.

Study programme

A common set of core modules in the autumn term ensures that all students obtain advanced knowledge in the fundamental areas of probability theory, statistical inference and applied and computational statistics.

A large and diverse set of elective modules is offered in the spring term, which provides the flexibility for you to develop your own specialist interests.

During the summer term, you complete a research project with a member of academic staff on a state-of-the-art research problem that suits your interests.

The assessment for your degree is made up of two-thirds core and optional modules, and one-third research project.

Professional accreditation

Our MSc in Statistics is accredited by the Royal Statistical Society .

Graduates from accredited degrees can apply to the Royal Statistical Society for the professional award of Graduate Statistician. Graduates from non-accredited courses may also apply for this status and will be considered on an individual basis.

Our accreditation agreement with the Royal Statistics Society is until the 2022-23 academic year.  The Department expects to be accredited into the future.

This course equips students with a range of transferable skills, including programming, problem-solving, critical thinking, scientific writing, project work and presentation. Many graduates go on to undertake roles in employment and research sectors.

Structure 

This page reflects the latest version of the curriculum for this year of entry. However, this information is subject to change.

Find out more about the limited circumstances in which we may need to make changes to or in relation to our courses, the type of changes we may make and how we will tell you about changes we have made.

Page last reviewed on 22 October 2021.

General stream

Core modules.

• Probability for Statistics
• Fundamentals of Statistical Inference
• Applied Statistics
• Computational Statistics

Statistics Research Project

Optional modules.

You choose five or six optional modules   from below to total 30–32.5 ECTS .

You can choose a maximum of two modules each worth 7.5 ECTS.  Each module is worth 5 ECTS unless otherwise stated.

• Contemporary Statistical  Theory
• Bayesian Methods
• Multivariate Analysis
• Machine Learning
• Introduction to Statistical  Finance
• Advanced Statistical Finance
• Biomedical Statistics
• Statistical Genetics and  Bioinformatics
• Advanced Simulation Methods
• Data Science
• Deep Learning with TensorFlow
• Nonparametric Statistics
• Stochastic Processes 
• Survival Models (7.5 ECTS)
• Time Series Analysis (7.5 ECTS)

You will complete an extensive research project full-time between May and September, with the opportunity to work with a member of academic staff on a state-of-the-art research problem that suits your interests.

You choose at least four modules from Group 1 and the remainder from Group 2  to total 30–32.5 ECTS .

• Introduction to Statistical Finance
• Contemporary Statistical Theory
• Statistical Genetics and Bioinformatics
• Stochastic Processes

Biostatistics

Core biostatistics modules.

You choose three or four optional modules from below for a total of 20-22.5 ECTS .

Core Data Science modules

You choose two optional modules   from below for  a total of 10-12.5 ECTS .

You can choose a maximum of one module worth 7.5 ECTS.  Each module is worth 5 ECTS unless otherwise stated.

Statistical Finance

Core statistical finance modules.

You choose any other modules from below  for a total of 15-17.5 ECTS .

You can choose a  maximum of two modules each worth 7.5 ECTS.  Each module is worth 5 ECTS unless otherwise stated.

Theory and Methods

You choose at least two modules from Group 1 and  the remainder from Group 2  to total 30–32.5 ECTS .

Group 1 

• Statistical Genetics and Bioinformatics 

Teaching and assessment

Teaching methods.

• Dissertation
• Group tutorials
• Modern statistical computing skills
• Office hours
• Oral presentation and assessment
• Practical computational sessions
• Problem classes
• Research seminars
• Virtual learning environment

Assessment methods

• Assessed coursework/tests
• Enhanced coursework assessments
• Oral presentation
• Written examinations
• Written project

Entry requirements

We welcome students from all over the world and consider all applicants on an individual basis.

Minimum academic requirement

Our minimum requirement is a 2.1 degree in statistics, mathematics, engineering, physics or computer science.

International qualifications

We also accept a wide variety of international qualifications.

The academic requirement above is for applicants who hold or who are working towards a UK qualification.

For guidance see our  Country Index  though please note that the standards listed are the minimum for entry to the College , and not specifically this Department .

If you have any questions about admissions and the standard required for the qualification you hold or are currently studying then please contact the  relevant admissions team .

English language requirement (all applicants)

All candidates must demonstrate a minimum level of English language proficiency for admission to the College.

For admission to this course, you must achieve the higher College requirement in the appropriate English language qualification. For details of the minimum grades required to achieve this requirement, please see the English language requirements for postgraduate applicants.

Competence standards

Our competence standards highlight the core skills students should be able to demonstrate by the end of this course.

View the Department of Mathematics's competence standards  [pdf]

We believe in providing the widest practicable access to all of our degree programmes and will make reasonable adjustments wherever possible to support your study. For more information, please contact the Department using the contact details below.

E:  [email protected]

How to apply

You may be asked for a short interview (in person or via Skype) as part of the application process. These will normally be reserved for applicants who have been out of education for a significant period of time or those who do not come from a background in Mathematics or Statistics.

Course choices

When you apply, you will be able to choose your stream of choice.

If you are applying for the general stream of this course, we are only able to consider your application if you choose this as your first course choice.

If you are applying for one of the specialisation streams, please select the stream as your first course choice and we will automatically consider you for the general stream if your chosen specialisation is full.

Making an application

Apply online.

All applicants must  apply online .

Visit our Admissions website for  details on the application process .

You can submit one application form per year of entry. You can usually choose up to two courses.

Application fee

If you are applying for a taught Master’s course, you will need to pay an application fee before submitting your application.

The fee applies per application and not per course:

• £80 for taught Master's applications (excluding MBAs)
• £135 for MBA applications

There is no application fee for MRes courses, Postgraduate Certificates, Postgraduate Diplomas or research courses, such as PhDs and EngDs.

If you are facing financial hardship and are unable to pay the application fee, we encourage you to apply for our application fee waiver. 

Find out more about the application fee and waiver

ATAS certificate

An ATAS certificate is not required for overseas students applying for this course.

Further questions?

Find answers to your questions about admissions. Answers cover COVID-19, English language requirements, visas and more.

Visit the FAQs

Tuition fees and funding

The level of tuition fees you pay is based on your fee status , which we assess based on UK government legislation.

Find out more about fees and funding opportunities .

• Tuition fees

Home rate of tuition

Fees are charged by year of entry to the College and not year of study.

Except where otherwise indicated, the fees for students on courses lasting more than one year will increase annually by an amount linked to inflation, including for part-time students on modular programmes. The measure of inflation used will be the Retail Price Index (RPI) value in the April of the calendar year in which the academic session starts e.g. the RPI value in April 2022 will apply to fees for the academic year 2022–2023.

Whether you pay the Home fee depends on your fee status.

Your fee status is assessed based on UK Government legislation and includes things like where you live and your nationality or residency status.

Find out more about how we assess your fee status .

EU/EEA/Swiss students

The Government has confirmed that EU/EEA/Swiss students who begin a course before the 31 July 2021 will be eligible to pay the same fee as Home students and have access to student finance for the duration of their course, as long as they meet certain requirements which are unchanged from previous years. This includes students who begin the course remotely.

EU/EEA/Swiss students starting a course on or after 1 August 2021 will no longer be eligible for the Home fee rate and so will be charged the Overseas fee. Please note, we do not expect this to apply to Irish students or students benefitting from Citizens' Rights under the EU Withdrawal Agreement, EEA EFTA Separation Agreement or Swiss Citizens' Rights Agreement respectively. However, we are currently awaiting the formal publication of the amended Fees and Awards regulations.

The UK Council for International Student Affairs (UKCISA) website has useful information on the conditions you currently need to meet to be entitled to pay tuition fees at the Home rate for study on a higher education course in England and reflect the regulations as they currently stand (not the amended regulations which are subject to publication).

Overseas rate of tuition

£30,500 for the General stream £30,000 for all other streams

Whether you pay the Overseas fee depends on your fee status.

Postgraduate Master's loan

If you're a UK national, or EU national with settled or pre-settled status under the EU Settlement Scheme, you may be able to apply for a  Postgraduate Master’s Loan from the UK government, if you meet certain criteria.

For 2022-23 entry, the maximum amount is £11,836. The loan is not means-tested and you can choose whether to put it towards your tuition fees or living costs.

Scholarships

We offer a range of scholarships for postgraduate students to support you through your studies.

See what opportunities you may be eligible for:

• Find scholarships from the Faculty of Natural Sciences
• Explore other scholarship opportunities

Accommodation and living costs

Living costs, including accommodation, are not included in your tuition fees.

You can compare costs across our different accommodation options on our Accommodation website .

A rough guide to what you might expect to spend to live in reasonable comfort in London is available on our Fees and Funding website .

Further information

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Enquiries E: [email protected]

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Lecturer (assistant professor) at Imperial College London

• Google Scholar

Hello and welcome! I am a lecturer (assistant professor) in the statistics section at Imperial College London. I obtained my PhD from the University of Toronto in 2022 under the joint supervision of Nancy Reid and Daniel Roy. My main interests lie in statistical inference in the presence of a high number of nuisance parameters, and computational statistics. I am also interested in inference problems in statistical genetics and astrostatistics. This website contains a list of my publications, talks and CV.

If you are interested in contacting me, my email is yanbo.tang[at]imperial.ac.uk.

Supervision

I supervise PhD students through the Mathematics Research Doctoral Programme, or through the EPSRC CDT in Modern Statistics and Statistical Machine Learning at Imperial and Oxford (StatML). The projects I offer are suitable for candidates with an interest in high-dimensional statistics or computational statistics and a good background in mathematical statistics. If you are interested in a PhD position under my supervision, contact me via email before submitting an application; please attach a copy of your CV and transcript to your email.

Programme in Statistics

Imperial College London

www3.imperial.ac.uk

The Times Higher Education World University Rankings is the only global university performance table to judge research-intensive universities across all of their core missions: teaching, research, knowledge transfer and international outlook.

Photos of university / #imperialcollege

The Statistics Section has an international reputation for conducting methodological and applied statistical research at the highest level. Particular areas of current activity include statistical genetics and biostatistics, statistical methods in retail financial services, time series, core statistical methodology, classification and data mining, with many interactions and overlaps between these areas of research. The Statistics section offers opportunities for PhD research in a variety of areas of statistics, as well as related topics (e.g., probability theory and signal processing). An overview of certain areas that the Section is particularly strong in may be found in the webpages of our research groups, although it is also common for both members of staff and PhD students to pursue research that does not readily fall under one of these headings. 

PhD research can be either full-time, normally taking between three and four years, or part-time, which takes at least four years. PhD candidates fund their studies in a variety of ways.  UK and European Union students are eligible for EPSRC DTA (doctoral training account) awards, of which the Department has a limited number available for offer: these cover College fees and (for UK students) maintenance.  

Research groups:

• Astrostatistics
• Bayesian Methods and Computation
• Dynamic Networks
• Machine Learning, Data Mining and Big Data
• Publications
• Statistical Genetics, Bioinformatics and Biostatistics
• Statistical Theory and Applied Probability
• Statistics in Retail Financial Services
• Time Series, Spatial Statistics and Signal Processing

In order to carry out research in statistics, you have to apply to the College for admission as a research student in the Department of Mathematics, specifying Statistics as your desired field of research.  We do not expect you to arrive with a fully formulated research programme in hand, but you should put some thought into the kind of topic you might be interested in pursuing, for example by checking the current research of the faculty members in the section, as presented on their home pages.  Members of the section are very happy to have informal discussions with you about current research opportunities.

We maintain close links with industry, and many students have been funded by bursaries provided by external organisations in return for which they spend some time working on projects related to their research.  Other students are funded by scholarships provided by a variety of private foundations, or by funds derived from research contracts. Some candidates are self-funded. 

PhD research can be either full-time, normally taking between three and four years, or part-time, which takes at least four years. 

Biostatistics

University of Cambridge

Genomic medicine and statistics.

University of Oxford

Pure mathematics and mathematical statistics.

University of Birmingham

University of Colorado at Denver

University of Toronto

Computational science and statistics.

South Dakota State University

Epidemiology and biostatistics.

University of Zurich

University of Geneva

Applied mathematics and statistics.

Johns Hopkins University

Deadline information.

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Thoughts on the msc in statistics.

I was accepted into the MSc in Statistics at Imperial College London. I wanted to know any general thoughts about the course from people who might be familiar with it. Any comment is welcome, though in particular thoughts about the course content, graduate prospective (either working at a company or pursuing a PhD afterwards) or experiences as an international student will be particularly helpful!! :) Thanks a lot!

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• Mathematics and Statistics

Top Stat PhD programs 2021

By Stat Phd March 6, 2021 in Mathematics and Statistics

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Hi all I’m applying this year to a PhD in statistics, and wanted an up to date list of the best PhD programs to apply for. 

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DanielWarlock

It depends on your research interest. I don't know what you want in terms of a "top list". There are numerous rankings out there, but they are overall ranking of the entire statistics department instead of a particular subfield, based on ranking criteria you might or might not think is relevant. 

That said, the newest ranking released 2021 is QS World University rankings by subject from 4 days ago. Under the "Statistics & Operational Research" subject, top 10 is

3. Stanford

6. Cambridge

7. Berkeley (UCB)

9. Georgia Tech

10. Imperial College London

Link:  https://www.topuniversities.com/university-rankings/university-subject-rankings/2021/statistics-operational-research

US news is really as good of a place as any. Then learn about the peculiarities of the programs to find the ones that fit your goals best.  There are no other worthwhile rankings, and if they were, they would probably just be someone on this forum doing a slight re-ranking of US News.

• Stat Phd and MLE

7 hours ago, DanielWarlock said: It depends on your research interest. I don't know what you want in terms of a "top list". There are numerous rankings out there, but they are overall ranking of the entire statistics department instead of a particular subfield, based on ranking criteria you might or might not think is relevant.  That said, the newest ranking released 2021 is QS World University rankings by subject from 4 days ago. Under the "Statistics & Operational Research" subject, top 10 is 1. MIT 2. Harvard 3. Stanford 4. ETH 5. Oxford 6. Cambridge 7. Berkeley (UCB) 8. NUS 9. Georgia Tech 10. Imperial College London Link:  https://www.topuniversities.com/university-rankings/university-subject-rankings/2021/statistics-operational-research      

Thanks. Indeed, Removing the non-US schools, the top 20 US are similar to the US news top 20.

US news for reference:

• University of Chicago
• University of Washington
• Carnegie Mellon

I think will create an overall ranking aggregating all rankings. 

12 hours ago, DanielWarlock said: 1. MIT 2. Harvard 3. Stanford 4. ETH 5. Oxford 6. Cambridge 7. Berkeley (UCB) 8. NUS 9. Georgia Tech 10. Imperial College London

I'm not sure how useful this is for stats specifically, as several of these programmes lack independent statistics departments (MIT has Mathematics, or Operations Research, ETH has Mathematics, Cambridge has the department of Pure Mathematics and Mathematical Statistics) so  a lot of these universities wouldn't suit someone who wanted to do statistics (esp applied statistics)

Here's my very affective (read unscientific, subjective) rankings from  stalking alumni placements and professor productivity. It's pretty much a reranking of US News with the added information of the tiers indicating where the big jumps in quality are. I think within tiers the choice doesn't matter too much.

Stanford Tier:

Stanford. Elite Top:

Berkley, Harvard, CMU, (Likely UChicago but I didn't research them)

Uwashington, Duke, Michigan, Columbia, Cornell, UNC

NCSU , TAMU, UT Austin, UCLA, Wisconsin

2 hours ago, trynagetby said: Here's my very affective (read unscientific, subjective) rankings from  stalking alumni placements and professor productivity. It's pretty much a reranking of US News with the added information of the tiers indicating where the big jumps in quality are. I think within tiers the choice doesn't matter too much. Stanford Tier: Stanford. Elite Top: Berkley, Harvard, CMU, (Likely UChicago but I didn't research them) Top: Uwashington, Duke, Michigan, Columbia, Cornell, UNC Up there: NCSU , TAMU, UT Austin, UCLA, Wisconsin

Probably Stanford on elite top too?

Just now, Stat Phd said: Probably Stanford on elite top too?

Pretty sure he means stanford is a tier above everyone else for stats.

• liyu and trynagetby

Not so sure why people think stanford is better than berkeley.  It is a smaller department than berkeley.  It is mostly theoretical.  Berkeley has much closer ties to EECS and does a lot more applied and methodological research Not getting into the politics of this however A lot of people have complained about the lack of diversity at stanford.  I have heard many female applicants accepted at Stanford have rejected it because of its diversity reputation.   I am not sure if they have ever had a black or Hispanic phd student at stanford.   

• speowi and insert_name_here

12 minutes ago, statsnow said: Not so sure why people think stanford is better than berkeley.  It is a smaller department than berkeley.  It is mostly theoretical.  Berkeley has much closer ties to EECS and does a lot more applied and methodological research Not getting into the politics of this however A lot of people have complained about the lack of diversity at stanford.  I have heard many female applicants accepted at Stanford have rejected it because of its diversity reputation.   I am not sure if they have ever had a black or Hispanic phd student at stanford.   

When people discuss rankings, the only relevant thing is how the program will affect your academic job prospects after.  You can do applied research at a lot of places and get great industry jobs, and you can be just as successful coming from Berkeley, but I don't see how one could argue that Berkeley is better.  Does Berkeley have even 3 statisticians that come close to Tibshirani, Efron, Diaconis, Hastie, Candes, Donoho in terms of influence?  This isn't a dig at Berkeley, so I'm genuinely curious as to why you think this and would be happy to change my mind if you presented some evidence.

1 hour ago, statsnow said: I am not sure if they have ever had a black or Hispanic phd student at stanford.   

I think two of their current first years are Hispanic. Not that it makes the department diverse, but it appears to be a change from previous years.

icantdoalgebra

2 hours ago, bayessays said: When people discuss rankings, the only relevant thing is how the program will affect your academic job prospects after.  You can do applied research at a lot of places and get great industry jobs, and you can be just as successful coming from Berkeley, but I don't see how one could argue that Berkeley is better.  Does Berkeley have even 3 statisticians that come close to Tibshirani, Efron, Diaconis, Hastie, Candes, Donoho in terms of influence?  This isn't a dig at Berkeley, so I'm genuinely curious as to why you think this and would be happy to change my mind if you presented some evidence.

Easy; Peter Bickel, Michael Jordan, Martin Wainwright. People like van der Laan, Bartlett, Brillinger, Aldous, Yu, and Pitman might not be as famous as those Stanford faculty that you listed, but its not like they are some random professors. How about Fernando Perez and his work on creating Jupyter Notebooks? Perhaps its not as much of a research accomplishment, but creating a widely-used software that makes performing statistics and data science easier is definitely worth quite a bit of influence.

I'm not trying to argue that Berkeley is better, in fact I agree that Stanford's program is better. However is it substantially better? I am skeptical. 

There is a valid point though, in that Berkeley's stats department has leaned more heavily towards machine learning recently and if you are a statistics purist you could reasonably make the argument that Stanford is substantially better if that is your criteria for evaluation.

• gouda91 , statsnow and bayessays

@icantdoalgebra  I don't disagree with anything you said.

I think rather than discussing program rankings we should make an advisors ranking, lol, but I guess that's too delicate of a topic even for an anonymous forum. 

On 3/7/2021 at 10:13 PM, Stat Phd said: US news for reference:

Is this the most recent 2020 rankings from US News? I can't seem to find their stats rankings after 2018.

(They only do grad program rankings every several years (4, maybe?), so 2018 should be the most recent)

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We have 86 Statistics PhD Projects, Programmes & Scholarships in the UK

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Statistics PhD Projects, Programmes & Scholarships in the UK

Phd in computing science - optimal mechanism design and active inference for advanced human-computer interfaces to machine learning, phd research project.

PhD Research Projects are advertised opportunities to examine a pre-defined topic or answer a stated research question. Some projects may also provide scope for you to propose your own ideas and approaches.

Funded PhD Project (Students Worldwide)

This project has funding attached, subject to eligibility criteria. Applications for the project are welcome from all suitably qualified candidates, but its funding may be restricted to a limited set of nationalities. You should check the project and department details for more information.

AMR pathogens in cystic fibrosis: Development of host-relevant models and discovery of antibiotic combinations

Competition funded phd project (uk students only).

This research project is one of a number of projects at this institution. It is in competition for funding with one or more of these projects. Usually the project which receives the best applicant will be awarded the funding. The funding is only available to UK citizens or those who have been resident in the UK for a period of 3 years or more. Some projects, which are funded by charities or by the universities themselves may have more stringent restrictions.

EPSRC DTP Studentship: Digital blood twin: Disease signatures from common blood markers in deep longitudinal data towards AI-led enabled personalised healthcare and predictive medicine

Funded phd project (uk students only).

This research project has funding attached. It is only available to UK citizens or those who have been resident in the UK for a period of 3 years or more. Some projects, which are funded by charities or by the universities themselves may have more stringent restrictions.

Machine Learning for Spatial Transcriptomics Analysis in Human Cancers: Tackling Limited Data Challenges

Phd scholarship in demography and spatial analysis, funded phd programme (students worldwide).

Some or all of the PhD opportunities in this programme have funding attached. Applications for this programme are welcome from suitably qualified candidates worldwide. Funding may only be available to a limited set of nationalities and you should read the full programme details for further information.

Social Sciences Research Programme

Social Sciences Research Programmes present a range of research opportunities, shaped by a university’s particular expertise, facilities and resources. You will usually identify a suitable topic for your PhD and propose your own project. Additional training and development opportunities may also be offered as part of your programme.

Human Appetite and Obesity

Development and implementation of a "talent, health and wellbeing monitoring system" for exeter city football club youth academy talent programme ref: 5149, advancing joint modelling methodology for clinical prediction, funded phd project (european/uk students only).

This project has funding attached for UK and EU students, though the amount may depend on your nationality. Non-EU students may still be able to apply for the project provided they can find separate funding. You should check the project and department details for more information.

PhD in Computing Science - Interactive Model-based Probabilistic Visualisations for Exploring Decisions

Leverhulme ‘space for nature’ doctoral scholars (phd or msc by research+phd) leveraging machine learning to assess the impact of other effective area-based conservation measures (oecms) on bumblebee populations in the uk, understanding barriers and facilitators to technology adoption among older adults: a mixed-methods approach, self-funded phd students only.

This project does not have funding attached. You will need to have your own means of paying fees and living costs and / or seek separate funding from student finance, charities or trusts.

Hybrid OFDM transmission system for connected autonomous vehicles

Development of methods to triangulate multiple sources of evidence., phd studentship in “statistical inference for ordinary differential equations using automatic differentiation.” (2024), phd studentship in the health economics group: investigating approaches to the estimation of lifetime progression-free and post-progression mortality rates in cancer patients.

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Featured Dashboard of the Month: Graduate Program Statistics

The purpose of the Graduate Program Statistics dashboard is to display current and historical admissions, enrollment, and degree completion data for UCF’s graduate programs.

The Admissions data is broken out into gender, ethnicity, average incoming GPA and GRE test scores. The Enrollment section includes overall counts, full-time vs. part-time students, online participation, gender, ethnicity and residency. Degree Completion data includes number of degrees awarded, GPA upon completion, and average number of years it takes students to complete the selected degree.

Data presented in the dashboard is available for current graduate programs at UCF, and it is updated each year in January and September.

The Graduate Program Statistics dashboard is open to the public and can be accessed from the Interactive Dashboards page: https://ikm.ucf.edu/facts/interactive-dashboards/

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Graduate Writing Center: Strategies for Writing About Statistics

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Presenter: Caroline Diehl, Psychology, Graduate Writing ConsultantLeezet Matos, Psychology, Graduate Writing ConsultantThis workshop will review how to report a variety of statistical findings in writing, including results from ANOVAs, linear and logistic regression, and t tests, as well as how to use APA formatting for statistics. We will also discuss how to present statistical findings clearly and accurately when writing results and discussion sections. 

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MRC GIDA 4-Yr PhD in Epidemiology

Scholarship overview, degree level.

Postgraduate doctoral

Full tuition fees at the home rate and a UKRI stipend of £21,237

Number of awards

Academic year, tuition fee status, mode of study, available to.

Prospective students

Application deadline

Additional information.

Scholarship page

[email protected]

Available to applicants in the following departments

• Infectious Disease

Eligibility criteria

Please note: This scholarship is not available to continuing students.

Application process

If you have any additional questions, please contact us at [email protected] .