Data Scientist Internship Programme

Data Scientist Internship Programme

LIDA launched its Data Scientist Internship Programme in September 2016, as part of its commitment to developing data science capability and driving multidisciplinary data analytics research.  Soon to be in its fifth year, the Programme currently has ten talented interns, drawn from a wide range of academic disciplines and backgrounds, who are passionate about finding data science solutions to complex, real-world challenges. They are currently working alongside researchers from across the University on a variety of projects

Applications for the fifth cohort of LIDA Data Scientist Internships closed on 17th July 2020. If you missed the opportunity to apply for this cohort, please bear in mind this is an annual Programme and we will be looking for interns again next year.

The Internship Programme provides the opportunity for interns to:

  • Own delivery of a data science project and get hands-on experience using real data
  • Establish links with project partners and work to provide solutions to real world challenges
  • Build skills and knowledge in advanced analytics
  • Participate in on-site and external training opportunities in statistical analysis, visualisation, research methods and computer programming
  • Work alongside leading scholars as part of the LIDA team and gain valuable work experience

My experience as a LIDA data scientist intern has been great. The internship has given me the opportunity to work in the field that I’m most passionate about, at the cutting edge of cancer research and artificial intelligence. Through my project on biomarker discovery in glioblastoma, I acquired skills and experience that will be of paramount importance in the next steps of my career.”

Stelios Theophanous, former Data Scientist Intern (2018-19) now undertaking a PhD in predictive modelling for cancer outcomes


“I have thoroughly enjoyed my time as a Data Science Intern. This program is exactly what I needed to combine my PhD research skills with industry projects. I am confident I will finish this year perfectly positioned for my next career move.”

Kevin Minors, former Data Scientist Intern (2018-19) now working as a Data Scientist at The Oakland Group


“I completed a LIDA Internship working with Sky Betting & Gaming to develop models to identify problem gamblers.  My time at LIDA was essential to my transition from academia to industry.  Working in collaboration with academic and industry partners allowed me to develop my understanding of business challenges, while maintaining a solid academic grounding.  Having the support of academic supervisors helped ensure my work was rigorous; an ethos I have carried over into my current role as a Data Scientist at Sky Betting & Gaming”.

Ed Berry, former Data Scientist Intern (2017-18), now working in the public sector


Wondering what our interns get up to here at LIDA? You can read a number of blogs from our current and previous cohort of interns below:

Intern Projects 2019/20

Patrycja Delong

Title: Changes in meat consumption patterns in the UK – investigation using loyalty card data

Abstract: Vegetarian and vegan diets are increasing in popularity in the UK. Main motivations behind these dietary choices include health benefits along with concerns for animal welfare and environment. Little is known however, on how people’s overall dietary patterns change when they reduce their meat consumption. Traditional food surveys can provide some information about global trends, but lack insight of changes in behaviour at individual level. Moreover, they suffer from non-response bias and inaccuracy in self-reported food consumption. Using customer transaction data allows us to observe changes in purchasing behaviour of a cohort of households over time.

Within this project we are going to apply machine learning techniques to identify households that reduce their meat consumption and examine the dietary patterns associated with that transition. This research is conducted in collaboration with Oxford University as a part of the Wellcome Trust funded LEAP project (

Intern Profiles 2019/20

Vijay Kumar

Academic and personal background

I joined LIDA as a Data Scientist Intern straight after finishing my BSc Hons in Physics. During this time, I undertook some computational physics projects and used data science in my studies. This involved using advanced statistics and methods such as Monte Carlo simulation. I always enjoyed my computational science modules and knew I wanted to grow in my technical computing abilities. I also enjoyed my experiences in research and contemplated undertaking a PhD.

But I joined LIDA as I wanted to gain hands-on experience working with real data on projects that will affect people’s lives. I am unsure whether I want to pursue a career in academia or industry, and I hope that working as a Data Scientist Intern will give me the experience to be able to make an informed decision about working in research whilst also giving me networking opportunities with people in industry. I believe that working at LIDA will give me the vital computational and soft skills needed to thrive in whatever I do.

What do you hope to get out of your internship?

I want to make full use of the training available to broaden my skillset. I would like to learn to use other coding languages such as R and Java as I believe it will help me be a better all-round professional. I am also very interested in data science techniques such as machine learning. I have been playing around with this in my own time, but I would love to see how machine learning can be implemented in a research environment on real data. This is something I would love to get stuck into as it has many implications in science and medicine.

Where do you see yourself in 12 months’ time?

In 12 months’ time I would hope to be starting a new job in industry or starting a PhD. I am not too sure what the future holds but I am reassured that working as a Data Scientist Intern at LIDA will give me the skills to be able to have options, and the experience to know where I am best suited.

See all

Early economic modelling and budget impact analysis of Prolaris® test to aid the treatment management decisions in prostate cancer patients

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Identification of Clinical Factors Associated with Poor Surgical Outcomes in a Primary Care Dataset

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Does fabric tactility affect clothing product sales?

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An area classification of consumer vulnerability in the UK

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Application of natural language processing for identification of online hate on Twitter

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Assessing the effectiveness of the e-petition procedure through Twitter conversations

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Catch! – real time simulation of daily travel patterns

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