Dionysis Grigoriadis is a senior bioinformatician based in London with 8 years of experience applying computational methods to NGS, WGS/WES, and methylation data for both research and clinical projects. He has implemented and optimized GATK best-practice pipelines, led GWAS and rare variant analyses within the Genomics England environment, and built a Flask-based app for accessible variant interpretation. His background blends hands-on molecular biology (CRISPR, RT-qPCR, flow cytometry) with software development in Python and R, enabling robust end-to-end study design and automation. At EMBL-EBI he contributed to WormBase Parasite, and he now applies that domain-scale experience at Constructive Bio. Known for turning complex genomics workflows into reproducible pipelines and lightweight tools, he pairs attention to detail with practical machine-learning applications for phenotype prediction. Colleagues value his ability to bridge wet-lab insight and scalable computational solutions.
8 years of coding experience
6 years of employment as a software developer
Integrated Masters Degree in Biological Applications and Technology Biology/Biological Sciences General, Integrated Masters Degree in Biological Applications and Technology Biology/Biological Sciences General at University of Ioannina
High School Ι, High School Ι at Arsakeio HighSchool of Thessaloniki
Master of Science - MS Bioinformatics, Master of Science - MS Bioinformatics at Queen Mary University of London
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