Research

Thesis title: "Decentralized Machine Learning Approaches for Toxicity Predictions"

Thesis outline: Aljoša Smajić is a PhD student in the MolTag program. The aim of his doctoral project is the establishment of novel paths for the creation of predictive models in the field of toxicity prediction. The results can address privacy and governance challenges and provide controlled, indirect access to large and comprehensive datasets for the development of ML & DL algorithms. He is, in addition to his doctoral project, involved in the eTRANSAFE project for the prediction of in vivo toxicity in humans based on animal testing data.

Supervisor & Co-Mentor: Gerhard Ecker

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