AI Upskilling & Support for Immunology Research Professionals
Expert training and support from computational immunologists with 10+ years experience across academia, biotech, and pharma.
Our Mission
We are computational immunology experts with over a decade of experience in developing and applying computational tools and pipelines across academia, biotech, and pharma. We bridge the computational gap by providing direct project support while upskilling immunology teams in the latest AI methodologies
Core Areas of Expertise:
Computational and Systems Immunology | Infectious Disease Biology | Comparative Genomics
AI | Machine Learning | Bioinformatics | Mathematical Modelling
Meet The Team
Jason Cosgrove, PhD
Systems Immunology and OncologyWe're computational immunologists with over a decade of experience working across academia, biotech, and pharma. Along the way, we've published in leading journals, secured major grants from funders like the ERC and Wellcome Trust, and managed a number of private-public research partnerships. We’ve also had to opportunity to teach and give practical workshops at institutes including Sorbonne University, Institut Pasteur, and University College Dublin. Now we're focused on helping others build these skills.
Our Collaborative Network Includes Researchers From:
Infectious Diseases & Comparative GenomicsThomas Hall, PhD
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.
