National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Clinical Trial Assistant (Undergraduate Placement Year)

The Institute of Cancer Research
Sutton
3 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Science Apprentice

Data Engineer

Data Engineer

Graduate Apprentice BSc (Hons) AI and Data Science-eHealth

Automation Analyst II – Enterprise RPA & Machine Learning Projects

The Institute of Cancer Research is looking for a Clinical Trial Assistant (Placement) to work in the Investigator Initiated Trials (IIT) Team, which is part of the Drug Development Unit (DDU). The post offers an enthusiastic and well-motivated individual a chance to work in a motivated and supportive academic team that are at the forefront of Phase-I cancer trials.

As Clinical Trial Assistant, you will be required to assist with central, remote and onsite monitoring, filing and administrative support to the Clinical Trial Managers, Clinical Research Associates, Clinical Data Analysts, Sample Coordinator and Pharmacovigilance officer.

Key Requirements

The successful candidate should be doing a medical, life science, nursing or pharmacy equivalent degree and looking for a placement year work experience (sandwich year) as part of the undergraduate degree. They should be motivated, be able to work independently, have excellent attention to detail, as well as being organised with good logistical/planning skills and be able to prioritise effectively. They should also be able to develop effective working relationships, have excellent verbal and written communication and good IT skills. It is also desirable that the applicant has experience of organising their own workload and some form of administrative or clerical experience or experience in maintaining efficient filing systems.

Department/Directorate Information:

Drug Development Unit – Investigator Initiated Trials team.

The Drug Development Unit, led by Professor Johann de Bono aims to seamlessly integrate preclinical drug discovery, proof-of-principle phase I trials and tumour-specific evaluation of novel agents. It is a conduit for the two-way communication between laboratory and clinical teams that is so essential for successful modern drug development. The unit conducts first-in-man phase I trials involving a range of targets, including growth factor or intracellular signalling, angiogenesis, apoptosis, epigenetics and DNA repair. All trials are underpinned by extensive analysis of biomarkers, both predictive and pharmacodynamics. The DDU includes The Oak Foundation Drug Development Centre (Oak Ward) housed within The Royal Marsden at the Sutton site and specifically designed for phase I clinical trials. Opened in February 2005, the centre provides 10 inpatient beds, five treatment chairs and two outpatient suites, and allows researchers to enter almost 300 patients onto phase I trials each year. This makes the unit one of the largest of its kind in the world. 

The DDU also has a portfolio of investigator-initiated phase 1 trials (IIT’s) of novel targeted agents and combinations of these, including those made available via Cancer Research-UK’s (CRUK) Experimental Cancer Medicine Centres (ECMC) Combinations Alliance. These studies are centrally managed by the IIT team within the DDU that performs those functions associated with sponsoring early phase trials including project management, monitoring, pharmacovigilance, database development and central data review. The successful applicant will support the Senior Clinical Data Analyst in overseeing data management activities of the IIT team. 

For more information on the department of Clinical Studies or the DDU, see:

https://www.icr.ac.uk/research-and-discoveries/icr-divisions/clinical-studies/the-adult-drug-development-unit-at-the-icr-and-the-rm

https://www.royalmarsden.nhs.uk/our-research/our-research-facilities/oak-foundation-drug-development-unit 

To apply for this post, please submit an online application including a supporting statement, detailing reasons why you are applying for the post and attach your CV.

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.

The Ultimate Assessment-Centre Survival Guide for Machine Learning Jobs in the UK

Assessment centres for machine learning positions in the UK are designed to reflect the complexity and collaboration required in real-world ML projects. From psychometric assessments and live model-building tasks to group data science challenges and behavioural interviews, recruiters evaluate your statistical understanding, coding skills, communication and teamwork. Whether you specialise in deep learning, reinforcement learning or NLP, this guide offers a step-by-step approach to excel at every stage and secure your next ML role.