Upcoming Training

Proteomics & Metabolomics
Ubuntu Proteomics Summer School
01 Feb 2026
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07 Feb 2026
The Protea Hotel by Marriott® King George
R11,000 - R13,000 excl. VAT • 700 - 800 EUR
ABOUT
The Ubuntu Proteomics Summer School is designed to advance proteomics-driven research across Africa by equipping postgraduate scientists with essential conceptual and practical skills relevant to both academia and industry. The programme offers a rich environment for collaboration, bringing participants together through meet-the-experts sessions, roundtable discussions, and poster presentations. Certificates of attendance are provided for personal training records.
The curriculum follows a parallel-track lecture format:
Concepts Track – An introduction to the foundations of mass-spectrometry-based proteomics, covering experimental design, sample preparation, quantitative LC-MS workflows, data quality control, processing, and annotation.
Applications Track – A practical guide to the strengths and limitations of quantitative approaches, using instrument-specific datasets to teach set-up, extraction, processing, and quality-assessment workflows.
For industry partners, the school provides a platform to engage with emerging researchers and leverage Africa’s unique biodiversity for collaborative work in disease detection, personalised medicine, food safety, and food security.
HOW TO REGISTER
Sorry you missed it! Registration is closed for February 2026 in George, but please register to be placed on the waiting list for the Summer School in the event a delegate is unable to attend.
THANK YOU TO OUR HOSTS & ORGANISERS
Resyn Biosciences, Evosep, D-CYPHR, ionopticks, ThermoFisher Scientific, OpenMS, ACGT, Separations, and Bruker, Mass Dynamics
LEARNING OBJECTIVES
Concepts Track: An introduction to the foundations of mass-spectrometry-based proteomics, covering experimental design, sample preparation, quantitative LC-MS workflows, data quality control, processing, and annotation.
Applications Track: A practical guide to the strengths and limitations of quantitative approaches, using instrument-specific datasets to teach set-up, extraction, processing, and quality-assessment workflows.
WHO SHOULD ATTEND?
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