Faculty 07 · Analysis · data overlay
Bioinformatics, AI & Lab Automation
The computational layer that now runs through every biotech programme: sequence and omics analysis, machine learning for proteins and strains, laboratory automation and the data infrastructure that turns a biofoundry into a self-driving lab — taught with reproducibility and data integrity throughout.
Departments
The faculty is organised into four departments. Each groups the courses that belong together.
Foundations
Programming, statistics and reproducible analysis.
Omics analysis
Sequence, genomics, transcriptomics and proteomics.
AI and machine learning
ML and deep learning for sequences, proteins and strains.
Automation and data
Lab robotics, self-driving labs, LIMS and FAIR data.
Awards in this faculty
Stack the courses into a recognised award — from a short certificate to a professional master.
Where it leads
- Bioinformatician
- Computational biologist
- ML scientist (bio)
- Automation engineer
- Research data manager
Questions it answers
- “How do I turn raw sequencing data into a decision?”
- “Where does machine learning genuinely help in the lab?”
- “How do I make an analysis someone else can reproduce?”
All 20 courses
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Instructors
Biographies are published once credentials are verified and the instructor has approved the profile.
How we select instructorsFor organizations
Any course or award in this faculty can run as a private cohort for your team, scoped to your processes.
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