Summary
Richard Gremmen is a bioinformatician and data engineer with 11 years of experience who blends hands-on .NET and Python development with applied machine learning and robust data management for genomics and public health. He has built and refactored reproducible sequencing pipelines (ATAC-seq, ChIP-seq, RNA-seq, Cut&Run) and supported downstream analysis and metadata practices across academic, clinical and industrial projects. Currently contributing to pathogen surveillance at the Dutch National Institute for Public Health, he pairs production-grade engineering with domain expertise in regulatory and research genomics. His background spans enterprise data governance and BI to computational biology, giving him a rare ability to translate complex research questions into maintainable, auditable pipelines and dashboards. Notably, his earlier work in viral ecology and single-cell transcription modeling informs a practical curiosity for bridging stochastic modelling and large-scale sequencing analyses.
11 years of coding experience
22 years of employment as a software developer
Master in Molecular and Cellular Life Sciences (Bioinformatics), Master in Molecular and Cellular Life Sciences (Bioinformatics) at Utrecht University
Drs Theoretical Physics, Drs Theoretical Physics at University of Groningen
Methods for information system development, Methods for information system development at Open Universiteit
Technische Universität Berlin