PGDip Bioinformatics
Course Overview
This Master's programme equips students with the advanced computational skills needed to analyze complex biological datasets, preparing them for careers or further graduate work in the omics-enabled biosciences. The curriculum is designed for both wet-lab biologists and computational scientists to thrive in the data-driven future of biology. Through hands-on projects and collaboration with world-leading faculty and industry partners, students gain practical experience tackling real-world research challenges.
Key Program Highlights
- Master statistics, computer programming, and data integration for multi-omics analysis (genomics, proteomics, metabolomics).
- Gain hands-on experience with revolutionary technologies like next-generation sequencing and CRISPR.
- Tackle a substantial independent research project and a collaborative group project with academic and industrial partners.
- Learn to analyze and interpret massive biological datasets using state-of-the-art machine learning and computational methods.
- Prepare for diverse career paths in both academic research and the rapidly growing biotechnology and pharmaceutical industries.
Course Overview
This Master's programme equips students with the advanced computational skills needed to analyze complex biological datasets, preparing them for careers or further graduate work in the omics-enabled biosciences. The curriculum is designed for both wet-lab biologists and computational scientists to thrive in the data-driven future of biology. Through hands-on projects and collaboration with world-leading faculty and industry partners, students gain practical experience tackling real-world research challenges.
Key Program Highlights
- Master statistics, computer programming, and data integration for multi-omics analysis (genomics, proteomics, metabolomics).
- Gain hands-on experience with revolutionary technologies like next-generation sequencing and CRISPR.
- Tackle a substantial independent research project and a collaborative group project with academic and industrial partners.
- Learn to analyze and interpret massive biological datasets using state-of-the-art machine learning and computational methods.
- Prepare for diverse career paths in both academic research and the rapidly growing biotechnology and pharmaceutical industries.
