Openings

The M4L Lab is looking for two Ph.D. students. The successful applicants will work with Dr. David Cereceda on interdisciplinary research topics that involve Computational Mechanics, First-principles calculations, and Machine Learning. The positions start as early as Fall 2023. Evaluations will start immediately until the positions are filled. Please, see the description of each position below.

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Position 1: Ph.D. student

Topic:  Physics-informed machine learning models of bio-inspired materials

The goal of the project is to increase the current lifespan of tooth restorations by creating and validating a bio-inspired approach that studies the mechanics of bonded interfaces.

Qualifications:

• Bachelor's or Master’s degree in Mechanical Engineering, Materials Science and Engineering, Computer Science, Physics, or related disciplines.

• Strong background in machine learning and deep learning is desirable but not required.

• Prior experience in numerical modeling with FEM (ABAQUS, ANSYS) is desirable but not required.

• Prior experience with High-Performance Computing is desirable but not required

• Willingness and motivation to work in a highly interdisciplinary field. 

Starting date: as early as Fall 2023.

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Position 2: Ph.D. student

Topic: First-principles calculations of structural fusion energy materials

The goal of the project is to investigate the mechanical response of tungsten-based alloys exposed to fusion-like environments by using first-principles calculations based on density functional theory.

Qualifications​:

• Bachelor's or Master’s degree in Mechanical Engineering, Materials Science and Engineering, Physics, or related disciplines.

• Prior experience in solid-state density-functional theory computations (VASP, QE).

• Prior experience with High-Performance Computing is desirable but not required

• Willingness and motivation to work in a highly interdisciplinary field. 

Starting date: as early as Fall 2023.

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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, English test scores (foreign applicants), 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-2023” (for Ph.D. position) in the subject line. Interested candidates are encouraged to submit these materials to Dr. David Cereceda before submitting the online application at Villanova University.