Project description
Heathy ageing and population stratification for individuals at high risk of developing diseases have been increasingly important in preventive medicine. The multi-disciplinary project aims to leverage bioinformatics and artificial intelligence techniques to engage large scale of omics and biomedical datasets (genetics, the gut microbiome, and multiple omics) to better identify individuals who at high risk of developing diseases and pinpoint molecular pathways that underlie healthy ageing. The project will be based on large amount of data collected in various human cohorts from Groningen, collaborators and publically available sources, including the LifeLines cohort, (www.lifelines.nl), the human functional genomics project (http://www.humanfunctionalgenomics.org), the UKbiobank (https://www.ukbiobank.ac.uk), the human phenotype project (https://humanphenotypeproject.org/home).
PhD students working on these projects will be expected to:
- Integrate and analyze the genomic-, metagenomic-, metabolomics- and proteomics datasets
- Perform big data analysis using advanced machine learning techniques
- Design, develop, implement and maintain new algorithms, applications and infrastructure components
- Summarize and report key analytical findings in both oral and written form at work meetings, at international scientific conferences and in scientific publications