NIHR Undergraduate Internships

We have funding from the National Institute for Health and Care Research (NIHR) Undergraduate Internship Programme to support an exciting opportunity for three undergraduate students to undertake internships at the Imperial Clinical Trials Unit (ICTU). We are seeking students who are interested in pursuing a career in applied healthcare research or clinical trials, and who have completed at least the second year or between the third and fourth year of a four-year programme.

The Imperial Clinical Trials Unit (ICTU) (https://www.imperial.ac.uk/clinical-trials-unit/) is a UKCRC fully registered clinical trials unit, bringing together academic, clinical and trial management expertise. Our collaborative approach aims to deliver world-class clinical trials spanning all phases and designs, encompassing a diverse range of therapeutic areas.

We are looking for three enthusiastic undergraduates with an interest in healthcare research to join our dynamic team at Imperial Clinical Trials Unit (ICTU) for eight weeks from July to the end of August 2026.

The role involves undertaking a research project (see separate Job Descriptions and Project Summaries), as well as opportunities to gain insights into some of the key roles in a clinical trials unit such as the role of an applied clinical trial statistician and clinical data specialist.

There will be opportunities to interact daily with trial statisticians as well as members of the trial operations team and to attend team meetings, seminars and research away days.

This provides an excellent prospect for the interns to develop knowledge in clinical trials and some of the key roles in healthcare research. Interactions with different research professionals will create networking opportunities and insights into potential avenues for future career options.

We are looking for three undergraduate students with a keen interest in healthcare research and desire to work in clinical trials.

To be eligible, you must be currently studying for an undergraduate degree and meet one of the following criteria by the internship start date (6th July):

• You will have completed the second year of your course, or
• You will be in the third year of a four-year course.

Your degree should be in one of the following areas, depending on the internship role:

• Clinical Trial Statistics Intern: statistics, mathematics, or a related quantitative subject

• Clinical Data Systems Intern: computer science or a related quantitative subject

The posts are not targeted at medical students.

A full list of essential and desirable criteria can be found in the Job Description & Person Specification for each of the three internships.

This post is full time (35h/pw) for a fixed term of eight weeks and will pay £21.60 per hour. The interns would be subsidised for up to £1000 for their travel and accommodation costs.

We are committed to inclusivity and equal opportunity. We therefore encourage applications from students of all backgrounds and underrepresented groups.

All three interns will be based at the Imperial White City campus.

Please submit your CV and cover letter by email to:  ictu-internships@imperial.ac.uk.

In the cover letter please outline how you meet the essential and desirable criteria, as applicable, and clearly state which role you are applying for in the subject of your email (Statistics Lit Review/Statistics Vit B12/Clinical Data Systems).

We also encourage applicants to complete our optional EDI survey after submitting their CV and cover letter. Responses to the survey will have no impact on the selection process or the decision to offer an interview.

Closing date for applications: 17 April 2026

Shortlisted candidates will be invited to attend an interview in the week of the 11^th  May 2026. Exact date to be confirmed. The interview will take place either online or in-person per the applicant’s preference.

Successful candidates will be in post by 06 July 2026.

Imperial College is committed to equality of opportunity, eliminating discrimination, and creating an inclusive working environment. We are an Athena SWAN Silver award winner, a Stonewall Diversity Champion, a Disability Confident Employer and work in partnership with GIRES to promote respect for trans people.

Lead supervisor: Louise-Rae Cherrill

Patient reported outcomes (PROs) in clinical trials are important to health policy makers, regulatory authorities and patients. PROs are essential in disease areas where few objective measures exist and are key for capturing patient experiences in most settings. PROs include patient assessments of symptoms, impact of illness on quality of life or wellbeing including aspects like fatigue, and general wellbeing. They are most often measured using validated instruments, like questionnaires and can be completed on paper, over the telephone and online.

Statistically, PROs are often ordinal variables but typically are treated as continuous for analysis. Ignoring the distributional characteristics of ordinal variables – ceiling and floor effects, bimodality and heavy tails – can lead to incorrect inferences. This is especially important when a PRO is used as a primary outcome in a clinical trial.

This project aims to assess the analysis of PROs in current practice. The intern will examine trial publications from the last 10 years that use specific PROs common to respiratory trials (COPD Assessment Test and PROactive Physical Activity in COPD) as primary or secondary outcomes.

Through the research project the intern will gain knowledge and experience in:
 - Performing a robust focused systematic review
 - An understanding of patient reported outcome measures in clinical trials
 - Performing a critical appraisal of published research
 - Summarising and presenting research findings within an academic environment

Through the applied project the intern will gain knowledge and experience in:
 - Reviewing clinical trial data
 - Utilising study resources, such as SAP, protocol and CRF

Please see the Statistics Literature review project JD and person spec for all details.

Lead supervisor: Emma Kirby

During the set-up of a new clinical trial the requirements for the EDC system are manually created from the study protocol and provided to the Clinical Data Systems (CDS) team for development. The CDS team take the requirements, review the protocol and clarify anything that is unclear and manually create eCRF form templates that are uploaded into the OpenClinica system. The process of creating the requirements and form templates is labour intensive and prone to human error. Technology has evolved to automate this process ensuring accuracy and efficiency. There will be elements of the development of the requirements and eCRF form templates that will need to be manually configured and finetuned but if the skeleton is already created by automation, this will allow more time for greater focus on these tasks. Clinical trial timelines are often short, and the EDC development comes at the end of the set-up phase. Improving the efficiency of the EDC development could substantially reduce the EDC go live timelines.

Project Overview
This internship will focus on applying scripting skills to generate clinical trial requirements from the protocol and also continue work already started on generating OpenClinica eCRF form templates from clinical trial requirements. This will therefore improve the accuracy and efficiency of the current manual processes. The intern will be provided with various learning objectives as well as encouraged to work independently to investigate novel ways in line with best practices for automation scripting.

The intern will share their findings at department meetings or as part of conference abstracts or journal publications.

The primary aim of this project is to empower the intern with hands-on experience in automated scripting with the intention of building an automated process for creating eCRF form templates which can be used as need in the future for clinical trial development.

This opportunity will also raise awareness for careers in clinical data systems research allowing the intern to gain an understanding of the impact these skills can have in a clinical research environment.

Please see the CDS Project JD and person spec for all details.

Lead supervisor: Dr Agnieszka Lemanska

Vitamin B12 is essential for the functioning of the nervous system and the production of red blood cells. In the UK and the USA, the prevalence of vitamin B12 deficiency is estimated to be around 6% among people under 60 and 20% among people aged 60 and over. Traditionally, intramuscular injections have been considered the most effective treatment for B12 deficiency caused by physiological disorders and malabsorption. Oral supplementation with tablets is a suitable option for individuals with deficiency linked to diet. Injections, however, are invasive and require appointments with healthcare professionals, whereas tablets are more convenient for patients and practitioners and cost-effective for the NHS.

The COVID-19 pandemic caused major disruptions in healthcare delivery, leading to rapid changes including an increase in remote consultations. COVID-19 interim guidelines recommended postponing injections or replacing with tablets to minimise in-person appointments. However, the evidence comparing the effectiveness of B12 injections and tablets across various conditions remains limited due to the small number, size, and quality of RCTs.

Project overview
Outcome Measures
The study will focus on the two main forms of vitamin B12 prescribed in the NHS:
 - Hydroxocobalamin, primarily available as injectable formulations.
 - Cyanocobalamin, mainly available as oral tablet formulations, although injectable forms also exist.

Statistical Analysis
Outcomes will be presented as:
 - Crude monthly prescription counts.
 - Rates per 100,000 registered patients across England.
 - Trends stratified by the seven NHS regions: Midlands, North East and Yorkshire, North West, South East, South West, East of England, and London.

Yearly counts and rates will be summarised using descriptive statistics. Monthly prescription counts and rates will be visualised using longitudinal plots. Linear regression will be used to model trends. Similar analysis has been conducted before (https://doi.org/10.1136/bmjopen-2024-093748) but it focused on primary care. The student on this project will access secondary care prescribing and will be responsible for updating the previous analysis.

Please see the Statistics Vit. B12 project JD and Person spec for all details.