Engineering/Aerospace and Mechanical Engineering, University of Notre Dame
We are currently recruiting several dedicated full-time postdoctoral researchers to work on “AI for Science” projects, focusing on scientific machine learning, data-driven modeling, and computational physics in general. Multiple positions are available, each with a specific area of focus outlined below:
Thrust 1: Computational modeling and analysis for steady-state and transient thermal conditions of nanoscale transistor and transistor array.
Thrust 2: Application of scientific machine learning techniques, such as physics-informed neural networks, Bayesian learning, data assimilation, and uncertainty quantification, to thermal analysis and predictive modeling.
Thrust 3: Computational modeling for solid mechanics, including finite element methods, composite materials, and related areas.
The primary objective is to develop predictive modeling capabilities for various physical systems, such as thermal dynamics of nanoscale transistors, mechanical analysis of fiber-reinforced composite materials, and other solid or thermal fluid systems. This will be achieved by leveraging experimental data, first-principle physics-based simulations, scientific machine learning approaches, data assimilation, and uncertainty quantification techniques.
Qualified Applicants:
- PhD in Engineering, Applied Math or a related discipline.
- Research experience in computational science and engineering.
- Ability to work independently and in teams.
Desired Qualifications (one or more of following):
- Experience with computational modeling of electron and phono transport
- Strong knowledge of thermal dynamics as applied to transistors.
- Experience with data-driven modeling and scientific machine learning (e.g., PINN).
- Proficiency in finite element methods and computational solid mechanics.
- Expertise in computational mechanics of composite materials.
Duration: One year, with possibility for extension based upon performance review and continuation of funding.
Application materials: please send the following documents to Prof. Tengfei Luo (tluo@nd.edu) and Prof. Jian-Xun Wang (jwang33@nd.edu)
- Resume/CV
- Contact information of three professional references.
