Elective module in High Performance Computing and Big Data Analytics. Thesis: Classifying Copy Number Variations using Machine Learning: A Comparison between XGBoost and TabNet.

Major Biological Data science and elective modules in Plant Biotechnology. Passed with 4 GPA. Thesis: Design of Artificial Metal-Binding Peptides by Neural Networks

High school education with focus on Natural sciences and Technology.

We founded an Escaperoom in Deventer. This was a personal project that I worked on with a few family members. While we started with with one escape room and only us (the founders) hosting our customers, we've expanded to six escape rooms and have over five workers spread between two locations in Deventer. My current responsibilities include hosting our customers, monitoring our social media accounts, performing administrative work, bookkeeping, designing and building escape room games, and, if necessary, performing repairs.

Commissioned projects:

• RIP-seq analysis to detect RNA-protein interactions involved with neuropathological diseases.
• Weighted Gene Correlation Network Analysis on 67 Tripterygium wilfordii samples to identify triptolide metabolic genes.
• Development of a machine learning classifier to detect copy number variations in targeted sequencing data.

I have worked with Sequentia Biotech on new techniques to detect Copy Number Variants (CNVs) in Next Generation Sequencing data. Statistical analysis and machine learning classifiers were at the heart of these technologies. The finished product consisted of a bioinformatic workflow that extracts important metadata from mapped sequencing reads and a deep learning classifier that predicts whether a region contains a CNV.

The Gezondheidsdienst voor Dieren (Animal Health Service, RoyalGD) is a leading organization in the Netherlands that focuses on animal health and production. I worked in an ISO 17025 accredited laboratory here, where I conducted routine analyses on animal-sourced samples. In addition, I contributed with the automation of the laboratory's data handling and processing.

I did my bachelor's thesis within the Department of Biochemistry and Microbiology. We researched whether it was possible to design novel proteins using machine-learning approaches. I developed a character-based Recurrent Neural Network (RNN) and trained it on all metallothionein peptides that are publicly available. I optimized the model to produce a variety of unique peptides while maintaining metallothionein activity.

KeyGene is a renowned plant research company based in the Netherlands that focuses on technology innovation for crop improvement . I was given the responsibility of screening a large mutant rice population for beneficial mutations. This was my introduction into the world of high-throughput research. To screen a dozen target genes, I used KeyGene's patented KeyPoint screening technique. I also developed and tested a new technique for detecting mutations in a three-dimensional pool of samples.

Maiden internship within the Membrane Enzymology group. The goal of this project was to use systematic mutagenesis to characterize the extracellular loop regions of a lysine-specific transporter in Saccharomyces cerevisiae. My responsibilities were making the yeast constructs and evaluating them with confocal microscopy and isotope uptake assays. The findings of this study are reported in the FEBS journal (link to publication)