|CCL 20.01.13 PhD student in Theoretical Chemistry and Machine Learning|
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To: jobs at ccl.net
Date: Mon Jan 13 15:24:15 2020
Subject: 20.01.13 PhD student in Theoretical Chemistry and Machine Learning
The QuNB group of Stijn De Baerdemacker (Canada Research Chair, Tier 2 in Theoretical Chemistry) from the Department of Chemistry at the University of New Brunswick (Canada) has a position for a PhD student available starting May or September 2020. Research in the QuNB group is situated around the development of electronic structure methods for finite-size and strongly correlated quantum many-body systems. Major research themes consist of geminal theory, beyond-integrability methods, density-matrix approaches, machine-learning methods, among others. More information on our research projects can be found on the website of the group http://www2.unb.ca/~sde6. Solving the quantum many-body problem remains one of the key challenges for the future. Many of the solutions to todays technological, medical and societal problems will be found in tomorrows smart devices, molecules and materials. Therefore, it is of utmost importance that we develop those theoretical and computational tools that will allow us to understand and predict the quantum properties driving those materials. Machine Learning methods are emerging as a new tool to provide accurate predictions for quantum mechanical observables. However, the inner workings of these methods however often remain mysterious, as it is not always clear how they arrive at a certain prediction. The purpose of this PhD project is to investigate the interpretability of Machine Learning methods for quantum chemistry. The PhD student will be directly involved with the development of (a) new Machine Learning methods for the quantum many-body problem, and (b) the tools to grasp a better understanding of the inner workings of these methods. The project will combine fundamental theoretical work with the implementation into efficient computational codes. The student will be able to enjoy access to high performance computing facilities and a strong international collaboration in North America and Europe. Interested applicants should be holder of a degree in chemistry, physics, mathematics or computer science, and be highly motivated to work in an interdisciplinary environment. Strong knowledge of quantum many-body theory, quantum chemistry or machine learning is an asset. Preliminary inquiries should be directed to stijn.debaerdemacker=unb.ca and should include a motivation letter and current CV. Formal applications must be processed and completed online at https://apply.unb.ca. Applications will be reviewed until the position is filled.
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