The Division of Computational Pharmacy, Department of Pharmaceutical Sciences, is offering a PhD student position to develop cutting-edge computational methodology and algorithms combining deep neural networks and detailed physicochemical modeling for drug discovery applications.
Computational methods have become an important pillar in structure-based drug design for accelerated identification and optimization of therapeutics. In addition to more traditional, physicochemical methods, recent developments in deep learning offer new directions in computational drug discovery. In our research group, we combine the best of both worlds, i.e. data-driven deep neural networks and detailed physicochemical models.
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