Scientist/Snr Scientist, Single cell genomics and Immunology

The immune system is a fundamental determinant of human health, governing resilience to infection and shaping susceptibility to disease and response to treatment. Advances in our understanding of immune function have catalysed some of the most transformative breakthroughs in modern medicine, underpinning a new era of immunotherapies and immune-based interventions. At IMU Biosciences, our mission is to decode the immune system at unprecedented resolution and translate these insights into meaningful clinical impact. By redefining immune measurement and interpretation at scale, we aim to advance precision medicine, develop diagnostics that enable earlier and more targeted intervention, and unlock novel strategies to harness immunity for the prevention and treatment of disease.

We are a multidisciplinary team of scientists, software engineers, and statisticians united by a shared ambition: to change the future of medicine through the power of immune data. We value diversity of thought, creativity, initiative, and a willingness to tackle hard problems in new ways. As an early-stage startup with state-of-the-art laboratories in central London, this is an exciting time to join IMU as we scale our platform and grow our team.

As a member of the Computational Immunology team your main focus will be on analysing and interpreting atlas-level single cell RNA-sequencing data, but will also include development and analysis of our deep immunophenotyping flow cytometry platform. This role will be solely dry-lab based but will involve extensive collaboration across the company, especially with members of our Laboratory and Data Platform teams.

We are seeking a highly motivated, enthusiastic, and dedicated person to join our Computational Immunology team. You will combine deep knowledge of theoretical and experimental immunology with strong data science and statistical modelling expertise, applied to truly population-scale single-cell RNA-sequencing and deep immunophenotyping datasets. The role will focus primarily on the analysis of large-scale scRNA-seq data, including the development, optimisation, and application of scalable analysis pipelines for cell state discovery, annotation, and comparative analysis across cohorts. You will lead exploratory analyses, develop novel methodological approaches, and identify robust biological signatures that inform downstream research and translational efforts. In parallel, you will contribute to the development and analysis of our deep immunophenotyping flow cytometry platform, with a clear emphasis on integrating flow-based immunophenotypes with transcriptional cell states to generate coherent multimodal insights.

In addition to hands-on analysis, you will play a key role in communicating results through clear written reports, internal presentations, and, where appropriate, external communications such as conference abstracts or publications. You will work closely with our laboratory team on experimental design and with our data platform team on infrastructure development and maintenance, ensuring analytical methods scale effectively with rapidly growing datasets. This is a hybrid role requiring regular onsite working at our central London offices.

Responsibilities

• Design, develop, and maintain scalable, reproducible scRNA-seq analysis pipelines suitable for cohort- and population-scale datasets
• Lead exploratory analyses, including cell state discovery, signature identification, and comparative analyses across cohorts, conditions, and demographic variables
• Perform and guide multimodal data integration across scRNA-seq and high-dimensional flow cytometry datasets
• Interpret analytical results in a biological and translational context, providing expert input to experimental, computational, and platform teams
• Stay current with developments in single-cell genomics, computational immunology, and related methods, and translate relevant advances into internal practice
• Prepare clear written summaries and presentations for internal stakeholders, including senior scientific leadership
• Contribute to manuscript preparation, conference abstracts, and external scientific communications where appropriate

The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope, purpose and grading of the post.

Skills, knowledge and experience

Essential Criteria

• PhD in a relevant discipline (e.g. immunology, bioinformatics, computational biology, systems immunology) plus:
• 0-2 years post-PhD experience in academia or industry for the Scientist II position, 3+ years post-PhD experience in academia or industry for the Senior Scientist position
• Strong grounding in immunology, with the ability to interpret single-cell data in a biological and disease-relevant context
• Demonstrated experience analysing scRNA-seq data at scale
• Experience working with multimodal or multi-omic datasets
• Proficiency in Python and/or R
• Hands-on experience with single-cell analysis frameworks such as scVI/scANVI, Scanpy, and/or Seurat.
• Competency with version control and collaborative development using git and GitHub
• Experience curating, analysing, and interpreting large, complex biological datasets (e.g. transcriptomics, cytometry, clinical or cohort metadata)
• Strong written and verbal communication skills, with the ability to work effectively across multidisciplinary teams
• Right to work in the United Kingdom

Desirable Criteria

• Experience with machine learning or probabilistic modelling frameworks (e.g. PyTorch, scikit-learn, scVI)
• Experience working in cloud or HPC environments
• Experience in secondary RNA-sequencing analysis e.g. fastq to count generation
• Experience building or maintaining production-grade pipelines (e.g. using Nextflow or similar workflow managers)

Benefits

• Fast-paced startup culture where everyone’s perspective truly matters
• Clear opportunities to grow with the company as it scales
• Competitive salary based on role and experience
• Annual bonus linked to company performance
• Opportunity to participate in the company’s employee share option scheme
• Benefits package including workplace pension, private medical insurance, life assurance, and income protection