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We are pioneers in the field of proteogenomics and artificial intelligence, dedicated to identifying and characterising small Open Reading Frames (smORFs) that play critical roles in fundamental biological processes.
Microproteins represent an exciting frontier in molecular biology, with recent discoveries revealing their crucial roles as master regulators across multiple biological systems. These previously overlooked molecules are essential for orchestrating metabolic regulation and energy homeostasis, modulating inflammatory signalling pathways and immune responses, and influencing cardiac function and disease progression.
We focus on unveiling the roles of microproteins in metabolic disorders and cellular energy metabolism, investigating their involvement in chronic inflammation and inflammatory diseases, and exploring their potential as therapeutic targets in cardiovascular disease.
This research sits at the intersection of basic science and translational medicine, with direct implications for improving human health.
Key Responsibilities:- Develop innovative computational pipelines integrating ribosome profiling (Ribo-seq), transcriptomics, and metabolomics data
- Apply and enhance existing smORF identification tools while developing novel AI-driven approaches to predict functionally important microproteins
- Lead the computational analysis of multi-omics datasets to prioritise disease-relevant microprotein candidates
- Design prediction models to identify microproteins involved in metabolism, inflammation, and heart disease
- Collaborate with wet-lab scientists to validate computational predictions and refine prediction models
- Contribute to the development of new algorithms for improved microprotein detection and functional annotation
- Participate in commercialisation activities and innovation development
- Present findings at international conferences and prepare manuscripts for high-impact publications
- Ph.D. in Bioinformatics, Computational Biology, Computer Science, or related field
- Strong programming skills in Python, R, or similar languages
- Experience with next-generation sequencing data analysis, particularly Ribo-seq
- Proficiency in statistical analysis and machine learning methods
- Demonstrated ability to develop and maintain computational pipelines
- Strong publication record in computational biology or related fields
