Senior Bioinformatics Scientist

Immunocore (NASDAQ: IMCR) is a pioneering, commercial-stage T cell receptor biotechnology company whose purpose is to develop and commercialize a new generation of transformative medicines which address unmet patient needs in oncology, infectious diseases and autoimmune disease. Our leaders in R&D are internationally recognised as some of the biotech industry's most successful drug developers. We are creating not just an environment where great minds can interact but an innovation powerhouse answering the big questions.

Focused on delivering first-in-class biological therapies to patients, we have developed a highly innovative soluble TCR platform. Our ImmTAX molecules underpin a new generation of precision engineered drugs that harness the immune system to treat a broad spectrum of diseases with high unmet medical need, including oncology, infectious diseases and autoimmune diseases.

At Immunocore, we recognize that our employees are our greatest asset. By embracing Science, Trust, Respect, Integrity, Diversity, and Entrepreneurship (STRIDE), we create an environment where collaboration thrives, ideas flourish, and transformative changes happen. We are dedicated to developing breakthrough therapies that transform patients' lives, advancing medicine, and supporting one another in these pursuits. As such, 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.

Responsibilities include:

• Providing focused bioinformatics expertise to support the analysis and data management of translational biomarker data.
• Thoroughly exploring publicly available data together with emerging data from Immunocore's clinical trials to provide new insights into mechanism of action, molecular heterogeneity of disease and novel targets.
• Conducting the analysis of transcriptomic and genomic sequencing data from our clinical trials.
• Complimenting and developing scientific hypotheses through the mining of public data and the design and analysis of in-house experiments.
• Developing custom-made tools and analytics to assist interpretation and data visualisation.
• Maintaining and increasing technical knowledge in relevant fields through self-study, observation, attending relevant conferences and training courses.
• Operating in accordance with the Company’s Health and Safety policies.
• Independently testing and leading lines of investigation in data analysis.
• Proposing new analyses based on emerging data and other related information.
• Establishing priorities for own work and team-based projects; making decisions on prioritisation based on the overall goals of the team, department and project.
• Acting as a mentor or manager to other colleagues, especially new hires, sharing scientific and company knowledge.
• Providing analysis of new techniques and theories from outside the Company to advance the way the company works.
• Championing and helping others to understand Health & Safety within the company, providing ad-hoc training as required.
• Communicating and presenting research findings at meetings with colleagues, senior management and partners.

Required skills and qualifications:

• Proficient in R/BioConductor, Linux OS and shell scripting bash.
• Proven programming ability (Knowledge of at least one language, preferably Python).
• Understanding of molecular biology, cell biology, immunology or related discipline.
• Significant experience of independent research in academic or industrial setting, or transferable skills gained from professional experience.
• Experience of building next generation sequencing (NGS) analytical pipelines.
• Led a project small team, formally or informally, including project management.
• Experience of developing databases, using SQL or similar, and pairing with a user-friendly interface.
• Mentored and coached less experienced colleagues in scientific practices and theory.
• Knowledge of machine learning, applied statistics or related field is a plus.
• PhD in a scientific discipline with a minimum of 2-5 years of relevant experience (post-doctoral experience may be included) - preferred.
• MSc degree or BSc degree with equivalent research or industrial experience specific to the role - required.