Turing Internship Network

Launched in July 2020, the Turing Internship Network is a national engagement scheme between our business partners and doctoral students across the UK who are studying any topic with a data science and/or AI focus. The Turing's role is to facilitate and convene, pairing internship projects put forward by industry with talented doctoral students. The business partners host, supervise, and provide a salary for the successful interns.



Testimonial from one of our 2020 interns


Current partner organisations

For the Turing Internship Network 2021 Spring round, we are currently recruiting for 11 positions spanning across different expertise areas and the different divisions of our two strategic partners: GCHQ (and NCSC) and Accenture (and Accenture Labs). 

The deadline for applications is

  • 22 February 2021 (11:59 GMT) for initial shortlisting
  • 8 March 2021 (11:59 GMT) for final shortlisting

We strongly encourage candidates to submit their applications before the first deadline, however we will consider for shortlisting all applications submitted before the final deadline. If potential applicants need to arrange for reasonable adjustments regarding their application and/ or interview process, please email us at [email protected] 

Applications now open


cyber logo

The UK's cyber security mission is led by the National Cyber Security Centre (NCSC), which is a part of GCHQ. NCSC is helping to make the UK the safest place to live and work online. We support the most critical organisations in the UK, the wider public sector, industry, SMEs as well as the general public. When incidents do occur, we provide effective incident response to minimise harm to the UK, help with recovery, and learn lessons for the future.

As a strategic partner of The Alan Turing Institute, GCHQ and hence NCSC is committed to the same equality, diversity and inclusivity values and is aligned with the Turing Research Agenda, already collaborating on Defence and Security research projects.


Building a state-of-the-art model of Domain Ownership for Public Sector Domain Discovery

NCSC is currently developing a Domain Discovery service that will help inform UK public sector organisation understanding their full estate of ‘owned’ domains. Since the data can be unstructured, NCSC is looking to improve the current methods for detecting domain ownership by using the website content and the links between websites. The project aims are improving detection accuracy and efficiency using domain features that have not been accounted for, while tuning the hyperparameter modelling to find the most optimal prediction model. The resulting model will be tested against provided ground-truth data and will be productionised to allow non-expert users run the analysis with minimal input. 

Ideal candidate skills: deep learning, Natural Language Processing, image analysis, graph node embedding methods

Two further positions are open for applications and these can be accessed by making an account or logging in the application portal.


accencture logo

The digital revolution is changing everything. It’s everywhere – transforming how we work and play. Join Accenture’s teams working at the forefront of data science. You will help transform leading organisations and communities around the world. Accenture is driving these exciting changes and bringing them to life across 40 industries in more than 120 countries. The sheer scale of our capabilities and client engagements and the way we collaborate, operate and deliver value provides an unparalleled opportunity to grow and advance.  


Deep generative networks for data imputation and labelling 

Deep generative networks are widely used in many subfields of AI and machine learning. More recently generative models using deep learning have been employed in a creative manner to generate new media (images, text and music) but they have also been applied to areas such as drug discovery and data synthesis.   

One of the major bottlenecks in machine learning is the quality and quantity of training data, with missing values and missing labels having major negative impacts on the quality of the training data. This internship will focus on building and validating deep generative networks for data imputation and for handling missing labels.   

Ideal candidate skills: Deep Learning (generative networks), Machine Learning, GANs, VAEs. 

Explanations for Neural Knowledge Graph Embeddings 

Knowledge graph embedding models are neural architectures designed to predict missing links between concepts in large-scale knowledge graphs. Accenture Labs adopt them in a number of applicative scenarios, such as drug discovery, personalised medicine, food and beverage, and workforce intelligence.  

The intern will be in charge of designing, implementing, and evaluating an explanation sub-system for neural knowledge graph embedding models. Such interpretable machine learning model will infer and explain facts from a graph of clinical, genomic, and behavioural data, in the context of a personalised medicine project. 

Ideal candidate skills – a subset of: Machine Learning, Deep Learning, Explainable AI, Knowledge Graphs, Graph Representation Learning, Knowledge Graph Embeddings, Graph Neural Networks 

AI Hypothesis Generation for Multidisciplinary Teams in Oncology 

Collaboration requires that we know our colleagues’ expertise and capabilities, and that we consider the useful intersections of those with our own knowledge, skills and objectives. Beyond just a handful of colleagues, this becomes intractable to do comprehensively.  AI does not yet match the deep thinking of human experts in most fields. But what it lacks in depth, it makes up for in coverage – and that’s the ideal complement to human thinking in scaling collaboration.   

With the guidance of experienced researchers at the Lab, the intern will focus on selecting well-suited AI-based approaches, then building and validating an early stage “proof of technology” for hypothesis generation in this context.   

Ideal candidate skills: Knowledge Graphs, Representation Learning, NLP, Software Engineering  

Designing and building  models using natural language processing techniques 

Natural language processing (NLP) is a powerful tool that big organisations use when providing a variety of products and services. There is promising potential around its abilities to help readdress and/or mitigate any challenges in customer satisfaction.  

This internship seeks to place an intern experienced in NLP on client teams looking at tackling customer satisfaction through understanding intents and sentiments in customer interaction. The intern is expected to join a team building an NLP model to address client challenges. 

Ideal candidate skills: Deep learning, NLP transformer-based modelling, API development or exposure, Text representation techniques 

Designing and building models using time series and convolutional neural networks

Traditionally time series forecasting has been dominated by linear models. Deep learning models offer a lot of promise for time series forecasting. Deep learning neural networks can automatically learn arbitrary complex mappings from inputs to outputs and support multiple inputs and output and handle temporal structures like trends and seasonality.  

The intern is expected to master convolutional and recurrent neural nets and will be involved in the selection and implementation process for the right algorithms and tools for time series forecasting tasks, as well training, evaluating and refining the proposed model. 

Ideal candidate skills: Time series, CNN, feed forward neural network 

Designing and building tools for responsible human and machine interaction 

The successful intern will work with clients to help them understand their changing relationships and experiences with data and work, with a focus on the practical application of changing behaviours. The intern will provide advice and practical output on questions like:  

  • How can organisations integrate analytics and data into the experience of work in their unique context?  

  • How should we help people adopt data and analytics solutions to make better decisions?  

  • What are people’s motivations, attitudes and barriers towards data and its value in relation to their work? 

The intern could have a multitude of backgrounds or be cross disciplinary, and the ideal candidate is expected to bring behavioural lens to the question of data and analytics. 

Designing and building quantitative models of responsible AI principles 

Responsible AI as a topic has become important in the world of machine learning and AI. The ethics of such technologies are constantly debated about on the grounds of fairness, accountability, transparency, and explainability, among others.  

The successful intern will work with Accenture’s Responsible AI team to build a measurement tool to come up with quantitative measures for each principle. It is expected that these measures may vary by use-cases, thus the intern will likely support the work involving the development of framework and method for employing this tool.   

Ideal candidate skills: Machine Learning, Responsible AI, Big data, API development or exposure 

Why apply?

The Turing Internship Network provides a fantastic opportunity for doctoral students to rapidly develop their academic skills in a real-world business setting. The scheme is currently dedicated to doctoral students who hold the right to work in the UK and whose doctoral studies involve a heavy component in data science, AI, mathematics and/or statistics.

"The Turing Internship Network provides an excellent opportunity to gain industrial exposure and to map academic research experiences to real-world challenges. I have a better understanding of the industrial challenges through this internship. It is a great experience to be able to solve real-world problems using my academic research skills."

Pauching Yap, 2020 Turing Internship Network intern

We are currently open for applications. For more information about the scheme generally, please see the FAQs below.


What is the rationale behind the scheme?

Due to an increasing interest for students in acquiring industry experience and business awareness, and for the business sector to address challenges using data science, we are motivated to ensure everyone benefits from the Institute’s unique position in linking businesses with academics. We are therefore extending our training leadership goal to support opportunities that tackle real-world challenges.

Who provides the internship roles?

By default, internships are provided and hosted by the Turing business partner who require data-driven academic expertise for their business challenges. In exceptional cases, industry-academic collaborations might be established, and these may involve Turing researchers. Such information will be provided in the role specifications.

Who are these internships aimed at?

In order to be eligible for a Turing internship, you must:

  • Be a current doctoral student enrolled in a UK-based university 
  • Be studying for a PhD that heavily uses methods or concepts from mathematics, statistics, data science, computer science, AI, ethics and/ or technology
  • Be in the active phase of your studies – that is, you should have already finished your first year of project work (that excludes any taught time, such as a MRes year)
  • Be able to pause your studies for the entire duration of the internship
  • Have significant programming experience and be confident in using relevant packages and toolboxes for the internship requirements. Most internships require knowledge of Python, however that may not always apply 
  • Have the right to work in the UK full-time
  • For certain internships, being a British Citizen is a requirement

Who is not eligible to apply for the TIN internships?

Unfortunately, the current scheme cannot accommodate:

  • Undergraduate or Masters students
  • Students who are not currently registered with a UK university
  • Students who are in their first year of PhD work
  • Students whose PhD projects or experience to date does not include a heavy component on quantitative and/ or analytical work
  • Students who require visa for their right to work, including students on Tier 4 study visa

What is the duration of an internship?

In the current recruitment round, all advertised roles have an expected duration of 6 months.

When do the internships start?

The current advertised internships are expected to start between March – June 2021, depending on the role (please check the brochure for information on each role) and depending on the availability of the successful candidate. 

Are the internships paid?

Yes, all internships are paid at a minimum rate of £30,000 per annum pro rata (stipulated by the programme). This is inclusive of London/Dublin allowance and relocation costs. 

Where are the internships taking place?

Ideally and if the government guidance allows it, the successful interns will be required to go the office of the employer. The location depends on the role, spanning from London, to Manchester and to Dublin. However, it is likely that the internships will start remotely and they may continue remotely depending on how the restrictions may change.

What do I need to do prior to beginning my application?

You should discuss the possibility of carrying out an internship with your supervisor(s) and/or host university department. Undertaking an internship will involve pausing your studies for the entire duration of the internship, ideally at a convenient time for your studies.

What does the application process involve?

You will need to provide personal details, information about the PhD programme you are enrolled in, details about your employment and education to date, as well as answer some questions that demonstrate your suitability and motivation for undertaking the internship project you choose. No CV or cover letter are required.

How can I find out more information about the roles and application procedure?

Please create an account / log in your account on our secure application portal. You will be able to view granular information on each role by clicking or downloading the TIN brochure. 

Can I send a speculative application if I do not fit the eligibility criteria?

Unfortunately, we cannot respond to or accommodate speculative expressions of interest for this internship scheme.

If I am successful with my application, will I hold any formal relationship with The Alan Turing Institute?

The Turing will not be directly involved with you and will hold no formal relationship, such as a contract or a direct affiliation for carrying out the internship. However, we will provide support with your application, we will ask you for testimonials at the end of the internship and we will invite you to select Turing Internship Network events.

Where can I submit any remaining enquiries?

If you still have any questions, please email [email protected]

If my organisation is interested in providing internships, how can I find out more information?

Please email [email protected] if you would like to find out more.

Equality, diversity and inclusion 

We hope that the Turing Internship Network will attract a diverse pool of applicants. All applications will be considered on their merits and project suitability. Applicants can be of any nationality (unless otherwise stated in the specific internship requirements) providing they have the right to work in the UK full-time, and applicants from under-represented groups are encouraged to apply. We welcome applicants from all UK-based Universities, or who have taken a career break prior to their PhD.

We are continuously working with our business partners to develop inclusive internships (such as part-time options), and we are welcoming interested applicants to let us know what work arrangements would suit them best.

The Alan Turing Institute is a Disability Confident organisation. As part of this commitment we recognise that there may be individual circumstances that we need to be aware of. We aim to accommodate specific needs and personal circumstances, but are reliant on applicants sharing this information with us. 

To discuss an adjustment to the application process please contact our team directly at [email protected]. There is also a section on the application form where applicants may make us aware of individual circumstances. 

We will treat any information you disclose to us as sensitive and will handle it in line with the Data Protection Act 2018. You can find out more information about how we handle your personal data in our Transparency notice (available on the application portal).

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If you would like to find out more about the previous in-house internship programme, please see testimonials and more here.