Christoph Ortner: Professor at Department of Mathematics, UBC Faculty of Science

I support public scholarship, e.g. through the Public Scholars Initiative, and am available to supervise students and Postdocs interested in collaborating with external partners as part of their research.

I support experiential learning experiences, such as internships and work placements, for my graduate students and Postdocs.

I am open to hosting Visiting International Research Students (non-degree, up to 12 months).

I am interested in hiring Co-op students for research placements.

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ADVICE AND INSIGHTS FROM UBC FACULTY ON REACHING OUT TO SUPERVISORS

These videos contain some general advice from faculty across UBC on finding and reaching out to a potential thesis supervisor.

Supervision Enquiry

If you have reviewed some of this faculty member's publications, understand their research interests and have reviewed the admission requirements, you may .

Graduate Student Supervision

Master's Student Supervision

Theses completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest theses.

Parameter estimation for many-body potentials (2023)

We are interested in exploring the laws of interaction between atoms and molecules. In this thesis, we construct a model to predict the many-body interaction potential between atoms, given the averaged total potentials in an atomic cluster. This is an inverse problem because we are fitting against averaged observations of energy between many-body interactions. In a simplified setting with identically and independently distributed data, and defining an averaged basis that has the appropriate orthogonal property, the inverse problem is well-posed and can be solved with the least squares approximations in a numerically stable way. We perform numerical analysis to estimate the parameters and study the convergence of the approximation. Two-body and three-body interactions potential are studied as a motivation to generalize the framework for higher-order many-body interaction potentials with tensor product bases in the future.

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Implementation of a nonlinear Atomic Cluster Expansion (2022)

In this thesis, we present a proof of concept implementation of linear and nonlinlear models based on the Atomic Cluster Expansion (ACE) introduced in [16]. We introduce machine-learned interatomic potentials and derive the ACE as an atomic descriptor. This produces a model linear in its coefficient that serves to approximate the energies and forces of an atomic configuration. We train its coefficients for Silicon, Copper, and Molybdenum, and analyze the fit accuracy for energiesand forces benchmark training sets [37]. Furthermore, we extend the ACE model to approximate energies and forces through a nonlinear combination of linear ACE models. We describe how to implement this model, and in particular, how to efficiently compute the derivatives, and present example results for the same data sets. We summarize the Julia implementation of these nonlinear models and provide an overview of the direction the code base will take in the future.

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