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[Research Internship] Model interatomic interact ... (No replies)
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Research overview Materials can be studied using computer simulation which enables one to probe the motion of each constituent atoms and to build correlations between the acroscopic properties and the microscopic behaviors. On the one hand, traditional uantum mechanics methods provide particularly accurate results up to the electronic structure of the material. Yet, the drawback of this method concerns its computational cost which prevents one from studying large system sizes and long time scales. On the other hand, effective potentials have been developed to mimic atomic interactions thereby reducing those issues. However, these potentials are often built to reproduce bulk properties of the materials and can hardly be employed to study some specific systems including interfaces and nanomaterials. In this context, a new class of interatomic potentials based on machine-learning algorithms is being developed to retain the accuracy of traditional quantum mechanics methods while being able to run simulations with larger system sizes and longer time scales.
Simulation project Using computer simulations, the student will construct a database that should be representative of the different interactions occurring in a specific material. Machine-learning potentials based on the least-angle regression algorithm will be trained and its accuracy will be studied as a function of the size and the complexity of the database.
Supervision and teaching The student will benefit from the supervision of Dr. Julien Lam who is currently a permanent CNRS researcher working at CEMES (Toulouse). His research is focused on the use of many types of computer simulations to study nucleation and crystal growth. The selected student will learn from a large number of research domains
especially machine-learning, atomistic simulations, statistical physics and computer programming. Because of the current pandemic situation, the internship could be done either on-site in the laboratory located in Toulouse or online.
Requirements
Bachelor or master students in physics or chemistry [Do not apply if you have a computer science or data science degree]
How to apply?
Interested candidates should email a cover letter as well as a CV through the following email address: "[email protected]". Title of the email must include "Research internship".