About this role
Go to the homepage of Grow at the University of Amsterdam - Postdoc on Quantum Bayesian Optimization for Molecular and Material Design /static/uploads/53 universiteit van amsterdam re c thayana taveres 24092020 2811.jpg Are you passionate about exploring the potential of Quantum Computing for Machine Learning in Molecular and Material applications? Do you enjoy doing cutting-edge research at the crossroads of Informatics, Physics, and Molecular Sciences? Postdoc on Quantum Bayesian Optimization for Molecular and Material Design Are you passionate about exploring the potential of Quantum Computing for Machine Learning in Molecular and Material applications? Do you enjoy doing cutting-edge research at the crossroads of Informatics, Physics, and Molecular Sciences? Postdoc on Quantum Bayesian Optimization for Molecular and Material Design In this pivotal postdoctoral position, you will explore and realize the potential of Quantum Computing to improve Machine Learning models to accelerate atomistic simulation and model molecular and material properties. You will focus on Quantum Optimization and in making the complexity of Quantum Circuits tractable, but you will be free and encouraged to propose and pursue novel directions. You will collaborate closely with the Quantum initiative of the Molecular and Material Design (MMD) technology hub , as well as with the Quantum Computing division of SURF and with the Dutch Institute for Emergent Phenomena (DIEP). You will be embedded in the Computational Soft Matter (CSM) Lab , a joint initiative of the Institutes of Informatics (IvI) , Physics (IoP) and Molecular Sciences (HIMS) . In this pivotal postdoctoral position, you will explore and realize the potential of Quantum Computing to improve Machine Learning models to accelerate atomistic simulation and model molecular and material properties. You will focus on Quantum Optimization and in making the complexity of Quantum Circuits tr...