Joint research
Co-designed studies with shared scientific leadership, defined authorship and agreed data governance from the outset.
Research collaboration
For researchers and universities
Academic collaboration with clear terms: defined scientific leadership, agreed authorship, and data governance settled before work begins rather than negotiated afterwards.
Areas
Where collaboration is possible
Cancer genomicsArtificial intelligenceBioinformaticsSingle-cell analysisMulti-omicsctDNA and liquid biopsyTumour evolutionBiomarker developmentClinical AIClinical trial matchingTranslational researchComputational oncology
Models
Forms of collaboration
Grant collaboration
Co-investigator or work-package roles in competitive grant applications, contributing computational and genomic method design.
Data analysis
Analysis of existing genomic, transcriptomic or multi-omic datasets, with reproducible pipelines and documented method choices.
Method development
Development and validation of computational methods for a specific biological or clinical question.
Clinical translation
Work on moving a computational or molecular finding towards clinical evaluation, including biomarker qualification pathways.
Academic–industry partnership
Structured collaboration between academic groups and industry partners, with clear intellectual property and publication terms.
Student and researcher mentorship
Supervision and mentorship of students and early-career researchers in computational oncology and cancer genomics.
Terms agreed in advance. Intellectual property, publication rights, data governance and authorship are settled in writing before work begins. This is more straightforward at the outset than after results exist.
Propose