Manager, Global Labeling Product Leader

Johnson & Johnson; Highgate; On-site; GBP 60,000 - 80,000; Full time

Job summary

A leading biotechnology firm in Highgate is seeking an intern to develop a data storage and retrieval strategy for clinical trial resources. The role involves using machine learning to analyze data. Suitable for those studying life sciences or similar. Familiarity with Python, SQL, and R preferred, but training will be provided. The placement is paid, offers 25 days of annual leave, and access to a socially active work environment.

Benefits

Paid placement with annual leave

Pension scheme eligibility

Access to Sports and Social Club

Qualifications

• BSc in life sciences or bio‑medicine is required.
• Interest in data science is crucial.
• Familiarity with coding in Linux environment is desirable.

Responsibilities

• Design and implement strategies for data management.
• Use R or Python for data exploration.
• Search for response signatures related to clinical outcomes.
• Employ machine-learning techniques to gain insights.

Skills

Interest in data science and coding

Familiarity with coding

Strong analytical skills

Organisational skills

Communication skills

Education

Currently studying towards a BSc in life sciences/bio‑medicine

Tools

Python

R

SQL

Job description

Job Summary

Immunocore has a substantial clinical trial data resource, combining trial outcome data with extensive RNA and DNA sequencing data. Work with it using classical techniques has been informative, but the nature of the data also makes it a promising candidate for the application of machine learning (ML) algorithms. The aim of this project is to develop a systematic data storage and retrieval strategy suitable for integration with ML tools, and then to use ML to glean novel insights into response signatures and factors linked to treatment outcome., Initially, to work with the team to design and implement a strategy for efficient management and storage of existing clinical trial data and DNA/RNA sequencing resources. This is likely to involve, but not be limited to, development of relational (SQL‑like) database(s), with the use of either R or python visualisation tools for description and exploration of the data. Subsequently, to utilise this resource (alongside other data, as appropriate) to search for signatures of ImmTAC‑mediated responses and links to clinical outcomes. Exploratory work may involve a range of tools, but it is anticipated that the project will employ machine‑learning techniques to glean novel insights. This is likely to rely largely on python tools (e.g. scikit‑learn, PyTorch).

Currently studying towards a BSc in life sciences / bio‑medicine or a similar discipline. This would suit someone with an interest in data science and coding. Some familiarity with coding and working in a Linux environment is desirable (the post will involve work in python, SQL, and R), but this can be taught during the placement. Please note this is a training course and fees apply.

Responsibilities

• Design and implement a strategy for efficient management and storage of existing clinical trial data and DNA/RNA sequencing resources, likely involving relational (SQL‑like) database(s).
• Use R or Python visualisation tools for description and exploration of the data.
• Utilise the created resource to search for signatures of ImmTAC‑mediated responses and links to clinical outcomes.
• Employ machine‑learning techniques (Python, scikit‑learn, PyTorch) to glean novel insights.

Qualifications

• Currently studying towards a BSc in life sciences / bio‑medicine or a similar discipline.
• Interest in data science and coding.
• Familiarity with coding and working in a Linux environment (Python, SQL, R) desirable.
• Strong analytical, organisational, and communication skills.

Benefits

• Paid placement with annual leave (25 days pro rata), pension scheme eligibility.
• Access to active Sports and Social Club with subsidised events.
• Opportunity to work with innovative science and corporate growth.

Equal Opportunity

Immunocore is proud to be an equal opportunity employer. We are committed to fostering an inclusive workplace where everyone feels valued, respected, and empowered. We encourage applications from individuals of all backgrounds, regardless of race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, or any other characteristic protected by law.