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Current Position

Assistant Professor in Computational Atomic-Scale Materials Science at the Cavendish Laboratory, Department of Physics, University of Cambridge

Find out more about our work at https://www.fast-group.phy.cam.ac.uk/.

Research

Water remains the most fascinating liquid in our world. In order to provide new insights into aqueous phase behavior, I am developing machine learning methodology trained on accurate electronic structure calculations. In close collaboration with experiment, I apply these models to water in complex environments. Overall, my research aims at the modelling of aqueous systems at previously unreachable accuracy to provide reliable structural and dynamical insights into the aqueous phase.


Education

Undergraduate

  • Ruhr-University Bochum, Bachelor (2013) & Master (2015) of Science in Chemistry
  • Stanford University, Visiting graduate student (2015) in the group of Prof. Thomas Markland

Postgraduate

  • Ruhr-University Bochum, PhD (2016-2019) in the group of Prof. Dominik Marx, Title: "Properties of Hydrogen Bonding at Ultra-low Temperatures in Bosonic Quantum Solvents"
  • École Normale Supérieure, Visiting graduate student (2016) in the group of Prof. Rodolphe Vuilleumier
  • Charles University Prague, PostDoc (2019) in the group of Dr. Ondrej Marsalek
  • University College London (2020), PostDoc in the group of Prof. Angelos Michaelides

Publications

Machine learning potentials for complex aqueous systems made simple
C Schran, FL Thiemann, P Rowe, EA Müller, O Marsalek, A Michaelides
– Proceedings of the National Academy of Sciences
(2021)
118,
e2110077118
Machine learning potentials for complex aqueous systems made simple
C Schran, FL Thiemann, P Rowe, EA Müller, O Marsalek, A Michaelides
(2021)
Correlated Particle Motion and THz Spectral Response of Supercritical Water
M Śmiechowsk, C Schran, H Forbert, D Marx
(2021)
Force-induced Catastrophes on Energy Landscapes: Mechanochemical Manipulation of Downhill and Uphill Bifurcations Explains Ring-opening Selectivity of Cyclopropanes
M Wollenhaupt, C Schran, M Krupička, D Marx
(2021)
High-dimensional neural network potentials for solvation: The case of protonated water clusters in helium
C Schran, F Uhl, J Behler, D Marx
(2021)
Converged Colored Noise Path Integral Molecular Dynamics Study of the Zundel Cation down to Ultra-low Temperatures at Coupled Cluster Accuracy
C Schran, F Brieuc, D Marx
(2021)
Transferability of machine learning potentials: Protonated water neural network potential applied to the protonated water hexamer
C Schran, F Brieuc, D Marx
– The Journal of Chemical Physics
(2021)
154,
051101
Manifestations of Local Supersolidity of $^{4}$He around a Charged Molecular Impurity
F Brieuc, C Schran, D Marx
(2020)
Transferability of machine learning potentials: Protonated water neural network potential applied to the protonated water hexamer
C Schran, F Brieuc, D Marx
(2020)
Deciphering High-Order Structural Correlations within Fluxional Molecules from Classical and Quantum Configurational Entropy.
R Topolnicki, F Brieuc, C Schran, D Marx
– J Chem Theory Comput
(2020)
16,
6785
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Telephone number

01223 336384 (shared)

Email address