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.
5 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
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.