Attention Mechanisms in Chemical Graph Networks

Cheminformatics › AI Chemical Graph Neural Network Research

Attention Mechanisms in Chemical Graph Networks

Interns will research and implement attention-based graph neural network architectures to improve interpretability of chemical predictions. They will focus on understanding which molecular substructures contribute most to model decisions, with applications in feature attribution and explainable AI for chemistry.

Choose your preferences above

Select Type, Mode and Duration to view available internship titles and fees.