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The Multiscale Modeling of Materials and Machine Learning Laboratory (M4L Lab: https://www.m4l-lab.com/) at Villanova University is looking for one Ph.D. student to work on interdisciplinary research topics that involve Computational Mechanics and Machine Learning. The positions start as early as Fall 2024. Evaluations will begin immediately until the positions are filled.
The main goal of the PhD project is to create and validate computational models to predict materials behavior across multiple spatial and temporal scales. In particular, we are interested in accelerating the discovery of high-entropy alloys and bio-inspired materials with superior properties by applying and developing different data-driven and physically-based approaches.
Qualifications:
· Master's degree in Computer Science, Mechanical Engineering, Materials Science and Engineering, Physics, or related disciplines.
· Active Learning, Bayesian Machine Learning, Scientific Machine Learning, Projection-based model reduction
· Prior experience with High-Performance Computing is desirable but not required
· Prior experience in numerical modeling with FEM (ABAQUS, ANSYS) is desirable but not required.
· Willingness and motivation to work in a highly interdisciplinary field.
Offer:
- Fully funded PhD tuition with a 12-month salary, $500 start-up grant, and health insurance.
- Support to obtain the visa required to study in the United States, if needed.
How to apply
Interested candidates are invited to email Dr. David Cereceda (david.cereceda@villanova.edu) with their latest CV, a statement describing their research experience and interests, B.S. and M.S. transcripts, and the contact information for 3 references, all as email attachments in PDF format. This and any other specific inquiries should be addressed with “#Name: Ph.D. applicant-Fall-2024 - FindAPhD” in the subject line. Interested candidates are encouraged to submit these materials to Dr. David Cereceda before submitting the online application at Villanova University.
About the Principal Investigator
Dr. David Cereceda is an Assistant Professor in the Department of Mechanical Engineering at Villanova University. Before joining Villanova, Dr. David Cereceda was a Postdoctoral Fellow with Prof. Lori Graham-Brady at Johns Hopkins University, within the Hopkins Extreme Materials Institute. His research at Hopkins is aimed at understanding the dynamic fragmentation of brittle materials under extreme loading conditions. Dr. David Cereceda received his Ph.D. in Nuclear Engineering from Polytechnic University of Madrid in 2015, under the guidance of Prof. Jaime Marian and Prof. José Manuel Perlado. His Ph.D. research, performed at Lawrence Livermore National Laboratory and University of California Los Angeles, was focused on the multiscale modeling of body-centered cubic metals like tungsten from atomistic to engineering scales. His current research focuses on facilitating the discovery, development, and deployment of next-generation structural and bio-inspired materials by creating and validating computational models that leverage physics-based and data-driven techniques.
Research website: https://www.m4l-lab.com/
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