Summary
Merve Uslu is an experimental microfluidics researcher and data scientist with five years of interdisciplinary experience bridging academic research and applied data work. Currently a Postdoctoral Research Associate at Duquesne University while also working as a Data Scientist at John Snow Labs, she blends hands-on microfabrication and microscopy expertise with practical ML/NLP and data-visualization skills. Her background includes developing novel droplet-measurement techniques for digital microfluidics, fabricating devices via photolithography/soft lithography, and applying materials characterization methods from SEM to XRD. As a freelancer she scaled to 35 clients in a year, delivering end-to-end data projects using Python, SQL, Tableau, and deployed ML toolkits like TensorFlow and scikit-learn. Comfortable moving between lab benches and production data pipelines, she brings a rare combination of experimental optics/materials experience and real-world data product delivery. Based in the Greater Düsseldorf area, she leverages this hybrid skill set to translate complex physical experiments into actionable data insights.
6 years of coding experience
6 years of employment as a software developer
Bachelor's degree Physics, Bachelor's degree Physics at Istanbul University
Doctor of Philosophy - PhD Physics, Doctor of Philosophy - PhD Physics at Gebze Technical University
English, Turkish, German