Curriculum Vitae | Gregor Simm — Research Associate in Machine Learning

Work Experience

Research Associate in Machine Learning, University of Cambridge, since 2020
Development of reinforcement learning approaches for molecular design in 3D
Postdoctoral Researcher, University of Cambridge, 2018–2020
Design of Bayesian deep learning models to accelerate the discovery of novel materials
Advisor: José Miguel Hernández-Lobato
Machine Learning Engineer, Semiconductor Research Corporation, 2018–2020
Multi-Objective Bayesian optimization method development for design space exploration of integrated circuits

Ph.D. Theoretical Chemistry, ETH Zurich, 2018
Thesis: Error-Controlled Quantum Chemical Exploration of Reaction Networks
Advisor: Markus Reiher
MSc. Interdisciplinary Sciences (with distinction), ETH Zurich, 2015
Focus: Chemistry and Physics
Thesis: Bridging the Gap Between Theory and Experiment Using Gaussian Processes, Harvard University.
BSc. Interdisciplinary Sciences, ETH Zurich, 2013
Focus: Chemistry.

Computational Resources, 100,000 GPU hours, EPSRC, 2021–2022
Early Postdoc.Mobility fellowship of the Swiss National Science Foundation, 2018–2020
Ph.D. Fellowship of the Fonds der Chemischen Industrie, 2015–2017
Best Poster Presentation, Swiss Chemical Society Meeting, Fall 2016
Master’s degree with distinction, 2015

IBM Research, Zurich (virtual), January 2021
Reinforcement Learning for Molecular Design Guided by Quantum Chemistry
Bjørk Hammer’s Research Group, Aarhus (virtual), December 2020
Reinforcement Learning for 3D Molecular Design Guided by Quantum Chemistry
Machine Learning and AI in (Bio)chemical Engineering, Cambridge, July 2020
Reinforcement Learning for Molecular Design Guided by Quantum Mechanics
Deep structures – Joint workshop by Alan Turing Institute and Finnish Center for Artificial Intelligence, Helsinki, December 2019
GraphDG: A Generative Model for Molecular Distance Geometry
Machine Learning and AI in (Bio)chemical Engineering, Cambridge, July 2019
Machine Learning for Chemical Reaction Networks
Microsoft Research Cambridge AI+Pizza, Cambridge, February 2019
Exploring Chemical Reaction Networks with Gaussian Processes
53rd Symposium on Theoretical Chemistry, Basel, August 2017
Automated Exploration of Complex Chemical Reaction Networks
Competence Center for Computational Chemistry Meeting, IBM Research, January 2017
Heuristics-Guided Exploration of Reaction Mechanisms

Mentoring: Supervised two master’s students during their research projects
Teaching: Teaching assistant for several lectures including general chemistry, inorganic chemistry, and computer science, since 2013
Programming languages: Python and C++
Databases: MongoDB, PostgreSQL
Administration of high performance computing facility (2015–2018)