History
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Experience
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	**Postdoctoral Researcher (11/2023 – Present)**
	`Fritz-Haber-Institut der Max-Planck-Gesellschaft <https://www.fhi.mpg.de/>`_, Berlin 
	Developed a machine learning force field methodology that integrates electronic structure information to accurately model coupled electronic and ionic charge transport, enabling large-scale molecular dynamics simulations of solid-state lithium-ion batteries. Work carried out within the `SolBat project <https://solbat.org/>`_.

	**Postdoctoral Researcher (12/2022 – 11/2023)**
	`ICAMS <https://www.icams.de/>`_, `Ruhr Universität Bochum <https://www.ruhr-uni-bochum.de/en>`_
	Built a machine learning force field framework(`ACE+Q <https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.9.033802>`_, based on the `Atomic Cluster Expansion <https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.9.033802>`_) to capture long-range charge transfer and electrostatics; implemented in TensorFlow within the pacemaker Python package; matched the accuracy of state-of-the-art approaches.
	
	**Scientist (12/2022 – 11/2023)**
	`ACEworks GmbH <https://aceworks.works/>`_, Bochum
	Extended the PhD-developed methodology to handle multi-component (binary) materials; delivered production-ready code to `Materials Design Inc. <https://www.materialsdesign.com/>`_.


Education
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	**PhD in Physics (12/2017 – 12/2022)**
	`ICAMS <https://www.icams.de/>`_, `Ruhr Universität Bochum <https://www.ruhr-uni-bochum.de/en>`_
	Doctoral student as a part of the `International Max Planck Research School for Interface Controlled Materials for Energy Conversion <https://www.mpie.de/2747306/doctoral_programme>`_ and working in the group `Atomistic Modelling and Simulation <https://www.icams.de/institute/departments-groups/atomistic-modelling-and-simulation/>`_ . Designed and implemented a machine learning force field framework for non-collinear spin-lattice dynamics using TensorFlow (`magnetic ACE <https://www.nature.com/articles/s41524-024-01196-8>`_); integrated within the `pacemaker <https://github.com/mttrin93/ace_plus_q>`_ Python package; achieved 2× accuracy improvement over prior models and enabled large-scale (4,000 atoms) simulations on the nanosecond timescale; built an ab initio magnetic structure training database comprising 70,000 entries.

	**MSc in Condensed Matter Physics (10/2015 – 10/2017)**
	`University of Trieste, Trieste (IT) <https://portale.units.it/en>`_
	Conducted first-principles DFT simulations of CO and CO₂ adsorption on metal-organic frameworks; quantified binding energies and vibrational properties to support experimental spectroscopic data.
	
	**BSc in Physics (10/2012 – 09/2015)**
	`University of Trieste, Trieste (IT) <https://portale.units.it/en>`_
	Developed a Fortran-based tight-binding framework to compute electronic band structure of 2D materials under applied magnetic fields.