Computational Immunology & AI Expertise on demand
We support your projects as expert collaborators - boosting your capacity in data analytics, AI, and computational biology as you scale.
Our Mission
Building an in-house team of experts with programming, analytical, AI and biololgy expertise is essential but costly. We help scientists scale their research by providing a range of services and trainings to make computational immunology and AI expertise accessible.
Core Areas of Expertise:
Computational and Systems Immunology | Drug Discovery | AI | Machine Learning | Omics Analysis | Data Strategy
Making Sense of Data:
A key challenge in contemporary immunology
Investors and funding bodies expect data and AI capabilities as standard but many immunologists have no formal training in these disciplines, and developing this capacity in-house is challenging, competitive and costly.
With over a decade of experience across academia, biotech, and pharma, we join your team as expert collaborators. Accessing our expertise early means faster programme development and fewer costly mistakes. Our flexible services mean senior computational biology and AI expertise is available on demand — whatever the project scope or budget.
How We Work
We operate as an extension of your team — not as external vendors offering template solutions. Whether you need strategic guidance on target prioritization, end-to-end multi-omics analysis, data packages to de-risk your next funding round, or upskilling for your scientists, we scale our involvement to match your needs. Your Questions, Answered
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There are 4 main points that make us different to other bioinformatics education platforms.
1) We started out as biologists and learned computer programming and statistics later on in our education. As such we know what it is like to learn new coding skills with no formal background and also have experience balancing wet lab biology with data analysis.
2) Because we specialise in immunology, we can offer deeper support and insights than generic bioinformatics trainings. We understand the data types, the workflows, and the questions that matter in this field—so our support is practical and immediately relevant.
3) We believe that researchers learn best when applying analysis techniques to their own datasets. Many tutorials use relatively ‘easy’ datasets in which the experiment is well designed and well annotated with a very clear biological signal. However in many cases, datasets are much more complicated and messy than this, so it is important to train using the types of data that you will actually encounter.
4) We have worked across different research settings, starting in academia and transitioning to the private sector. As such we are well equipped to know what skills you need to develop to help land your first major research position in industry.
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Not necessarily. We offer courses ranging from "absolute beginner" to "advanced." Each course description clearly outlines the prerequisite skills required, but our foundational modules are specifically designed for biologists with zero coding background.
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Our curriculum primarily focuses on R and python, as these are the industry standards for biological data analysis and bioinformatics pipelines. For certain analyses it can also be interesting to combine both languages together using for example the reticulate R package. This allows users to merge the best of both languages.
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Yes and this is highly encouraged! We believe that by learning using relevant data, you will be able to apply your skills much more quickly to your research project. Importantly, all data is considered private to the researcher and will not be used outside of the scope of the learning session
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Absolutely. We provide tailored management and AI upskilling trainings as well as group training packages designed to upskill your entire team. For academics we also offer a grant writing and review service and can provide a discounted rate for select academic partners. Please contact us via our contact page to get a custom quote.