Summary
Dzvinka Yarish is a machine learning researcher and engineer with a decade of experience applying ML to bio- and cheminformatics, currently pursuing a PhD and working as a Junior Research Fellow at the University of Tartu. Her work focuses on predicting the effects and mode-of-action of genetic variants, combining computational genomics with deep learning and reinforcement learning approaches to improve drug discovery workflows. She has practical industry R&D experience building ML solutions for pharmaceutical use cases at SoftServe and has taught machine learning courses, bridging research and applied engineering. Notably, her background spans NLP, IoT, and genetics-enabled ML, giving her a rare cross-domain perspective that informs efficient exploration strategies in deep RL and variant effect prediction.
10 years of coding experience
5 years of employment as a software developer
Lviv Academic Gymnasium
Bachelor's degree, Computer Science, A, Bachelor's degree, Computer Science, A at Ukrainian Catholic University
Master's degree, Computer Science, Master's degree, Computer Science at University of Tartu
ukraininan, English, German