Degree: PhD or MD-PhD
Nationality: International Students
Application deadlines: Fall 2023/Spring 2024
Our overall research goal is to construct robust and comprehensive process-structure-property relationships to conduct systematic process and materials design for advanced manufacturing processes. To do so, we develop and integrate novel multiscale multiphysics simulation models and physics-informed machine learning models at different time- and length-scales. Current primary research topics include but are not limited to:
• Multiscale multiphysics modeling and simulation for metal additive manufacturing
• Physics-informed machine learning
• In-situ process monitoring and control for digital twins in metal additive manufacturing
Binghamton University is a world-class public ivy institution that unites more than 130 broadly interdisciplinary educational programs with some of the most vibrant research in the nation. It is classified among “R1: Doctoral Universities – Very high research activity”. Binghamton University is ranked tied for 35rdamong public schools, ranked as the best SUNY school for 2022 by U.S. News & World Report. Our unique character – shaped by outstanding academics, facilities and community life – promotes extraordinary student success. Binghamton merges rigorous academics, distinguished faculty and state-of-the-art facilities to engage and challenge its 18,000 students.
Named for the founder of IBM Corp., the Thomas J. Watson College of Engineering and Applied Science at Binghamton University was founded in 1983. Today, Binghamton is home to the fastest-growing engineering school in New York state, offering innovative bachelor’s, master’s and doctoral programs in 10 fields of study to over 3,100 students. Annually, Watson has over 2,000 bachelor’s, 425 doctoral and 625 master’s students from over 50 countries.
- This position is focused on the multiscale multiphysics modeling and simulation for metal additive manufacturing.
- B.S. or M.S. in mechanical/aerospace/civil engineering, materials science, applied mathematics, applied physics, or a closely related discipline. M.S. with project experience and publication record is preferred.
- Be passionate and self-motivated to do important/revolutionarywork in the aforementioned research topics.
- Strong background and interest in computational materials science, metal additive manufacturing or process monitoring.
- Good programming skills in C/C++, Fortran, Python, or MATLAB. Experience in GPU or parallel computing is a plus.
Interested candidates are invited to email Dr. Dehao Liu ([email protected]) with a short introduction of your research interests, the latest CV (including GRE/TOFEL scores and contact information of three professional references), and transcripts. GRE score is optional.