The M4L Lab is looking for four Ph.D. students. The successful applicants will work with Dr. David Cereceda on interdisciplinary research topics that involve Computational Mechanics, First-principles calculations, Nuclear Science and Engineering, and Machine Learning. The positions start as early as Fall 2024. Evaluations will start immediately until the positions are filled. Please, see the description of each position below. (as early as Fall 2024)
Position 1: Ph.D. student
Topic: Materials Informatics
The main goal of the PhD project is to accelerate 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:
Bachelor’s or 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
Willingness and motivation to work in a highly interdisciplinary field.
Starting date: as early as Fall 2024.
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 2024.
Position 3: 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 2024.
Position 4: Ph.D. student
Topic: Transmutation and energy spectra of first wall components during fusion reactor operation
The goal of the project is to create an integrated thermomechanical model of first-wall components under the evolving chemistry and microstructure of fusion energy reactors.
Qualifications:
Bachelor’s or Master’s degree in Nuclear Engineering, Materials Science and Engineering, Mechanical Engineering, Physics, or related disciplines.
Strong background in Nuclear Science and Technology.
Prior experience in neutronics, inventory evolution from transmutation, and pka energy spectra 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 2024.
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-2024 – Position #(indicate number 1,2, or 3)” in the subject line. Interested candidates are encouraged to submit these materials to Dr. David Cereceda before submitting the online application at Villanova University.
