Further projects open now for application to CDAS

Six further CDAS projects are now open for applications for the third cohort of students based at the Universities of Leeds and Manchester. We will also be advertising projects at the University Sheffield shortly along with further projects at Leeds and Manchester.

The projects are all partnered with an external organisation giving you the opportunity to work closely with industry. Opportunities range from using police data to understand violence, to working with Engineering consultants on using artificial intelligence to improve traffic safety.

We are looking for graduates from a wide range of backgrounds with interests in how data can be used to address social science questions using statistical or predictive techniques. You will work with a multi-disciplinary team of supervisors as well as having the opportunity to work with external partners on real life problems.

The programme is an integrated one (+4), where you will undertake an MSc in Data Analytics over the first two years which will provide you with the foundation skills to complete your research project.

Details for all available projects can be found on our available projects page

Please email datacdt@leeds.ac.uk if you wish to be notified when more projects are advertised.

University of Leeds projects

University of Manchester projects

Projects now available at the University of Liverpool: Application deadline 7th April

Five new CDAS projects are now open for applications for the third cohort of students based at the University of Liverpool. We will also be advertising projects at the Universities of Leeds, Manchester and Sheffield shortly.

The projects are all partnered with an external organisation giving you the opportunity to work closely with industry. Opportunities range from using police data to understand violence, to working with Engineering consultants on using artificial intelligence to improve traffic safety.

We are looking for graduates from a wide range of backgrounds with interests in how data can be used to address social science questions using statistical or predictive techniques. You will work with a multi-disciplinary team of supervisors as well as having the opportunity to work with external partners on real life problems.

The programme is an integrated one (+4), where you will undertake an MSc in Data Analytics over the first two years which will provide you with the foundation skills to complete your research project.

Details for all available projects can be found on our available projects page

Liverpool projects:

Counting People

Human Dynamics within an Urban and Regional Context

Improving the Geolocation of Emergency Service Response through Big Data

Using big data to design resilient coastal cities

The Geodemographics of British Streets


Please contact us with any questions

CDAS first Annual Partner Event

On the 18th September, the Centre for Data Analytics and Society held its first annual partner event at the Leeds Institute for Data Analytics (LIDA). Attended by academics from across the CDT institutions and representatives from partner organisations, the event proved a great opportunity for networking and for the students to share what’s been keeping them so busy in their first year.

The event was opened by LIDA Director, Professor Mark Birkin, who was key to the establishment of the CDT. It was then over to the students from each of the CDT institutions at the Universities of Leeds, Manchester, Liverpool and Sheffield. The students gave group presentations showcasing their learnings from the MSc modules, experiences of working with partners during internship projects, and how they’d already started applying their new data skills to their PhD topics. With research areas ranging from health to crime, transport, retail and more, the students displayed a broad use of data science techniques such as clustering and text analysis, including some ‘just for fun’ projects like Keiran’s analysis of Pokémon characteristics. The presentations gave a real flavour of the interdisciplinary nature of the CDT and a clear sense of collegiality was on show.

Marking the completion of the first year for the Data Analytics and Society CDT, the event also provided an opportunity for feedback and discussion from student, academic and partner perspectives. We’re excited that the ideas raised during the event have led to the launch of our new @DataCDT twitter page and the set-up of thematic interest groups to promote collaboration and knowledge-share across the institutions. We feel that this is especially important now that the CDT has grown in number, having recently welcomed a brand-new cohort of first year students.

Having completed day two of the Introduction to Programming module in Python, the new student cohort later joined the event for an informal poster and networking session. This was a chance to view academic posters prepared by each of the current students and to ask questions about their work and experiences so far, which seemed to fuel excitement and settle nerves in equal measure among the new students.

As the CDT enters its second year, we’re excited to work with new academics and partners and to see ongoing projects progress. A number of our students have already been getting out to share their preliminary research findings at conferences nationally and overseas. So, watch this space and follow our twitter page to stay in touch with our CDT students as they continue to work at the cutting edge of their subject areas.

Vicki Jenneson

Presentations from the students are below and posters from this event can be found on this page – https://datacdt.org/meet-the-students/student-posters2018/

CDAS Leeds presentation

CDAS Sheffield presentation

CDAS Manchester Presentation

CDAS Liverpool presentation

Centre for Data Analytics and Society welcomes its second cohort of students

We are the second cohort of the Data Analytics and Society CDT funded by the ESRC based in the University of Leeds; Maria, Debbie, Sedar, Caroline, Colin and Lena. The other CDT students are spread over the other partner universities, the University of Sheffield, the University of Manchester and the University of Liverpool. For us at Leeds, projects cover a wide range of topics, from energy footprints to consumer data for health, cycling infrastructure, data assimilation challenges and development of policy simulations. For this we have teamed up with partners including Improbable, CycleStreets and Dietary Assessment Ltd.

Mimicking the first cohort’s structure, we began with an intensive programming for social sciences module using python. This was taught at Leeds and is part of the integrated MSc. It was a great introduction to python for those who have not used this programming language previously and a refresher for those who have. This module set us off to a good start into our studies and we consider it a significant stepping stone towards further skill development.

Starting new programmes can be difficult, but with Vicki, Annabel, Jennie, Fran, Eugeni, Ryan, Keiran and the rest of the LIDA staff guiding us through our first few weeks here, we have been able to settle into our places at the university and LIDA easily. We look forward to what these next few years will bring.

CDAS student awarded best presentation at Nutrition Futures conference

Victoria Jenneson presented at Nutrition Society’s Nutrition Futures conference, for the student section of the society and received an award for the best presentation. Vicki gave a 3 minute lightening talk entitled “Systematic review of electronic sales data in population dietary surveillance”, outlining the purpose of the review and her findings on her PhD project so far.  The abstract for my work will be published in the Proceedings of the Nutrition Society.

Vicki said:  “I received some really lovely feedback from fellow students on how I told a story and engaged people in my research, so I’m really grateful for the presentation training we received earlier in the year from Simon Cain at Westbourne Consulting. The Nutrition Futures event concluded yesterday with talks on presentation skills, career planning, effective networking and a careers panel. I really enjoyed it and I hope to get more involved in Nutrition Society events in the future.”

End of year CDAS Update from the Students at Sheffield

And saving the best until last, hello from Sheffield. We’re the fourth and final group to make our introductions; Gioia, who’s working with Linney, Mike who’s partnered with Costain and Rhiannon who’s using data provided by South Yorkshire Police to examine crime harm and hotspots.

The final module hosted in sunny Sheffield brought us all back together for the week. Working in RStudio the Social Analytics and Visualisation course utilised a wide range of expertise from a number of disciplines starting with data visulisation delivered by Dr Mark Taylor from the SMI in his inimitable style. We were then introduced to machine learning by Dr Petar Milin from the Department of Journalism and by midweek we were text mining as Prof Paul Clough from Sheffield’s iSchool introduced us through sentiment analysis using Trump’s speeches. We were then very fortunate to have Dr Nema Dean from the University of Glasgow’s School of Mathematics and Statistics take us through statistical social network analysis. This packed week was then rounded off with an opportunity to speak to lecturers one on one and leave the course confident about the assessment.

Before the new academic year starts we will have the opportunity to share our progress at an event hosted at LIDA where we will be discussing our work though posters and group presentations. We’ll also be meeting the new cohort of students and their data partners. As we move into the second year and the focus of our time is directed more towards our Phd’s we look forward to working more closely with our own data partners and using the skills we’ve developed through our MSc modules.

CDAS Update from the Students at Liverpool

Welcome! We would like to introduce ourselves as the first cohort of the CDT in Data Analytics and Society at the University of Liverpool. Susie, who is working with Local Data Company on micro-location retail topologies. Nicola is working with Red Ninja using sensor data to analyse urban mobilities. Mel is working with Ordnance Survey on extracting data from aerial imagery. Nikos is also working with Ordnance Survey on defying neighbourhood trajectories in the UK. Krasen works with Carto on applying topology to urban data. Natalie is working with Boots on incorporating weather into sales forecasting methodologies. Céline is working with ShopDirect to examine the dynamics of pricing elasticities in the online retail environment.


We are a part of the Geographic Data Science Lab, (https://www.liverpool.ac.uk/geographic-data-science/ ) here at Liverpool’s Department of Geography and Planning. The lab researches many interesting topics, combining the fields of Data Science and Geography to develop innovative applications and outputs. Particular research themes include: urban and regional dynamics, the morphology of cities, investigating new methodologies and geographies of resilience, difference, exclusion and opportunity.


Last semester, we had the opportunity to undertake an internship with our partner companies. Collaborating on a research proposal laid the foundations for a healthy, communicable relationship with our partners, which we are excited to develop over the coming years of our PhDs. Some of us had the chance to work on our projects in-person in the company’s offices; a valuable insight into the inner working environment. Overall, we achieved a clearer picture of what our partners expect from us and how our project could benefit them.


Over the Easter break, we welcomed our fellow CDT students from the Universities of Sheffield, Manchester and Leeds for a short course in Practical Data Science in Python taught by Dr Dani Arribas-Bel. The course utilised a hands-on approach to help us grasp the steps involved when using datasets to solve real-life problems. These include data structuring, manipulation, visualisation, unsupervised learning algorithms and modelling. We also had the freedom to explore our own choice of datasets, giving each of us the opportunity to apply our new skills to topics that we find interesting and which relate to our PhD projects.


Overall, it was a valuable and transferable learning experience, which we very much enjoyed spending with our fellow Data CDT cohort. We will be looking forward to seeing everyone again for the final full-cohort module at the University of Sheffield in June.

New year, new challenges: The data CDT goes to Manchester

Hi, we’re Noelyn, Jen, Oliver and Chris, the first Manchester cohort of the Data Analytics and Society CDT. We are based within the Social Statistics department at Manchester but are also part of the Data Science Institute; comprised of over 600 researchers and methodologists across the Science and Engineering; Humanities; and Biology, Medicine and Health Sciences faculties.

At Manchester, our partner organisations are the market research and data analytics firm YouGov; Medical Data Solutions and Services and the Burns and Plastic Surgery Service at the University Hospital South Manchester; The Greater Manchester Health and Social Care partnership; and the Vegetarian Society. It’s exciting to be part of a cohort working on diverse projects ranging from examining and predicting political attitudes by combining survey and social media data; using machine learning to predict and classify healthcare outcomes; developing data science methods of evaluating the impacts of devolving healthcare spending; and using survey and social media data to explore social and psychological influences on dietary choices.

While our research is still in its early stages, we are looking forward to carrying out internships at our partner organisations in the next couple of months and putting the data skills and knowledge we’ve been developing as part of the CDT into practice in a ‘real world’ context.

Recently all the CDT PhD students from Leeds, Sheffield, and Liverpool travelled to Manchester for the Understanding Data and Their Environment module. With Professor Mark Elliot from the Data Science Institute and Dr Nuno Pinto from Urban Design and Urban Planning, over a week we explored issues relating to data anonymisation and deidentification processes, security and disclosure control and the complex legal and ethical issues surrounding these.

Later in the week, with guidance from Dr Yu-wang Chen from the Alliance Manchester Business School we also learned a lot about data pre-processing methods, different approaches to linking databases and strategies for dealing with some of the inherent difficulties in data integration.  We then had the opportunity to put our newfound skills into practise in group exercises looking at sales forecasting and classification for business analytics and combining socioeconomic data to look at factors which may affect life expectancy in London. Overall it was a challenging but enjoyable week – it was great to catch up with CDT students from the other universities and share our experiences of being PhD students so far, so we’re looking forward to the next CDT module in Liverpool in March.

Keiran Suchak Reports Back on CDT visits to Cambridge and Manchester

The first semester of the Doctoral program has been busier than I think most of the Leeds cohort of the CDT were expecting. With commitments to a module on Research Methods, demonstrating courses for undergraduates and working on the assignments for Andy Evans’ programming module, each of us looked forward to the end of semester. With the end of term came an end to taught modules, as well as an outflux of the university’s undergraduate population. This also coincided with a visit from members of the Office of National Statistics, who operated a Safe Researcher Training course. The aim of the course was to educate on the ethics of working with social data, the risks involved and how these could be mitigated. The day-long course was very interactive, and was liberally scattered with group exercises that allowed us to further explore the ideas that were presented, as well as challenging our own preconceived ideas.

The end of term also freed up time to organize a first meeting with my external project partner – Leeds City Council. Up until this point, I had been predominantly focused on the academic aspects of my project – the mathematics, the programming, the data analysis – that my brain had been trained to see over the course of my degrees in Physics and Mathematics. However, it was at this meeting that it became immediately apparent how broad the scope of application of my work would be. This meeting also allowed for the discussion of the variety of data sources that would be available to me, as well as scoping out ideas for an internship project that I look forward to undertaking this semester.

Following the end of term, I travelled down to Cambridge to attend a training week run by the Academy for PhD Training in Statistics. The aim of the week was to provide two intensive courses: one on Statistical Computing and the other on Statistical Inference. This week brought together students from universities across the UK – a variety which was matched by the range of subjects in which students were doing their PhDs, from medical statistics to climate science. Learning such a volume of material in such a compressed time-period was quite a challenge, but the exceedingly high quality of lecturing and evening activities that had been organised helped to make the week a very enjoyable experience.

A Shiny app used on the Statistical Computing section of the courses in Cambridge, which was designed to examine the convergence of different numerical solvers.

Fortunately, this week was followed by the Christmas break – with the office closed over this period, we had no choice but to down our tools and take some well-earned rest (as well as polishing off a couple of assignments). Returning in the new year, we submitted our assignments and ventured over to Manchester for a week, where we met with the students from the other universities for the second of our joint modules. The topic of this week was Managing Data and Their Environment – a subject that we quickly learned encapsulated a wide variety of topics. The week was split into three parts: the first couple of days were devoted to the ethics and implications of using social data, the next couple of days focused more on the processes of data cleaning and linkage, and the final day was dedicated to a groupwork project whereby we could put into practice the ideas that we had learned about over the course of the week. The section on the usage of social data closely mirrored portions of the Safe Researcher Training course, and so many of the group found this to be a rather familiar exercise. The section on data cleaning and linkage, on the other hand, was found to be a little tougher owing to the volume of new information that we had to take in; I was fortunate to have spent a significant portion of the time that I was employed at Ampere Analysis working on data matching and linkage, however, there was still plenty of new material to absorb.

An example of the data flows created in SAS Enterprise Guide as part of the data cleaning and matching section of the Manchester module.

The challenges of the days were washed away by evenings spent exploring Manchester – the highlight of which was a visit to Tampopo where we enjoyed a variety of Asian food.

With the end of January comes the start of the second semester: a return to taught modules, supervisor meetings and demonstrating along with the new challenge of an internship with our respective project partners. This semester promises to be even busier than the last, however, I am sure that each of us are looking forward to the challenges that await us over the coming months.

Author: Keiran Suchak