Joint Research Projects

Translational Cell Biology    

Integrates stem cell biology, biomaterials science, and immunology to understand cell–environment interactions and translate this knowledge into regenerative and immune-based applications

Focus Areas

• Generation, characterization, and application of stem cells.
• Understanding fundamental interactions and cellular aging
• Creating functional biomaterials with specific biological activities.
• Expanding uses for cell-derived biomaterials and extracellular
• In Vitro Models: Mimicking mammalian cell-bacteria interfaces for targeted research.
• In-depth analysis of immune system mechanisms and responses.
• Strengthening research translation and fostering collaborative

Cancer Biology and Drug Discovery   

Vertically integrated programme spanning mechanisms à biomarkers à targets à molecules, translating mechanistic insight into precision oncology solutions.

Focus Areas

• Multi-modal genetics/epigenetics and RNA-based biomarkers (liquid biopsy)
• Epigenetic networks and vulnerabilities in haematologic and solid tumours
• Drug resistance mechanisms and repurposing opportunities
• Novel anticancer drug candidates and targeted delivery strategies
• Redox-active agents and enzyme-based prodrug strategies
• Selective targeting via membrane trafficking and signalling
• TLR (toll-like receptor) spatial organisation and anti-tumour immunity

Neuroscience   

Integrating molecular, cellular, systems and behavioral neuroscience to understand brain function across the lifespan and its disruption in disease.

Focus Areas

• Identification of biomarkers and mechanisms of brain diseases (molecular, electrophysiological and gut–brain interactions)
• Neurobiological basis of cognitive functions and behaviour (perception, learning, adaptation, addiction, impulsivity, pain)
• Mechanisms underlying nervous system function across the lifespan (development → maturity)
• Mechanisms of electrical signalling and their link to functionality (ion channels, cellular excitability, cross-system principles)
• Development of novel AI-assisted analytical tools for electrophysiological and imaging data integration

Microbe-Virus Interactions   

Investigating host–virus conflict, viral diversity, and molecular innovation to enable targeted control of bacterial populations and development of novel molecular tools.

Focus Areas

• New bacterial defence and anti-defence systems
• Viral triggers of immunity
• Antiviral signalling networks
• Links between prokaryotic and eukaryotic immunity
• Novel Molecular Tools from Phages and Mobilome
• Biology and evolution of microbial viruses
• Exploration of phage diversity and highly diverged viral proteins
• Understanding microbe–virus interactions
• Nanostructure engineering

Microbial Adaptation and Disease   

Investigating microbial adaptation, pathogen evolution, and host–pathogen dynamics to understand antimicrobial resistance, chronic infection, and emerging disease threats.

Focus Areas

• Resistome Dynamics. Horizontal gene transfer and emergence of resistance.
• Opportunistic Pathogen Establishment. Evolution and long-term adaptation within human hosts.
• Virulence & Immune Evasion. Mechanisms of pathogenicity and treatment avoidance
• Selective Pressures in Chronic Infection. Host immunity, antibiotics, and within-host heterogeneity.
• Viral Diversity and Evolution. Comparative genomics and metatranscriptomics.

Biodiversity and Ecology   

Integrating biodiversity science, evolutionary biology and ecosystem research to understand organismal adaptation and ecosystem resilience under environmental change.

Focus Areas

• Biological processes shaping organismal adaptation, and environmental health
• Genetic and physiological bases of stress resilience using advanced sequencing, mutagenesis, functional genomics, and electrophysiology to inform climate-resilient agriculture and species management
• Organismal responses to environmental change (migration, adaptation, phenotypic plasticity)
• Impacts of pollution on ecosystems, climate processes, and human health

Molecular Biotechnology   

Develops next-generation protein-based solutions—from engineered enzymes to antibody-guided systems—enabling sustainable bioprocesses and advanced molecular diagnostics

Focus Areas

• Protein interaction prediction and modelling (protein–ligand/substrate, protein–protein, protein–lipid interactions)
• Catalytic bioprocess efficiency and optimization
• Recombinant protein production systems
• Targeted molecular tools for diagnostics and therapies

Genome Editing and Epigenetics   

Next-generation programmable genome and epigenome editing systems by making delivery, target recognition, and editor function fully programmable

Focus Areas

Programmable delivery systems

• Pooled nanoparticle screening
• Generative phage mutant design
• Phage-host interaction profiling

Programmable epigenetic marks

• Orthogonal writer engineering
• Effective functional group installers
• Processive editors

Tuneable and programmable transcriptomic regulation

• Tuneable CRISPR regulation
• Combinatorial perturbation screens

Structural and Computational Biology   

Integrating structural biology and computation to understand biomolecular mechanisms and enable predictive molecular design.

Focus Areas

Experimental structural biology

• Solving structures of interesting biological molecules
• Investigating mechanisms of biomolecular complexes formation
• Single-molecule and single-cell approaches

Computational structural biology

• Predicting structures of biomolecular complexes
• Analysis of biomolecular structures
• Development of scientific software (both command line and web-based)

Data-driven research and infrastructure for data

Data-driven inference and prediction (new methods, machine learning, AI, large scale analysis)

Multi-Modal Single-Cell Biology   

From single-cell multi-omics to explainable AI-driven models of cellular identity and disease.

Focus Areas

• Emerging Single-Cell Multi-Omics Technologies. Development of bespoke high-density single-cell and multi-modal assays capturing transcriptomic, epigenomic and regulatory layers.
• Multi-Modal Data Integration. Integration of chromatin state, nascent RNA, DNA methylation and protein-level data into unified cellular profiles.
• Large-Scale AI-Driven Inference. Application of neural networks (transformers, VAEs) for cross-modality prediction and mechanistic modelling.
• Multi-Modal Biology of Human Health. Translational application of single-cell multi-omics and AI to disease mechanisms and biomarker discovery.