1. Research Assistantship (RA) for a PhD Student in Mechanical Engineering|
An NSF-funded research assistant position is available for a new PhD student in Mechanical Engineering at the State University of New York (SUNY) at Binghamton. The research is focused on materials printing using a hybrid inkjet-electrospray technique. The goal is to print highly-ordered monolayers of functional nanoparticle inks at high throughput. The student’s research will be experimental; however, close collaboration is expected with faculty and students in materials science and computational physics. Specific tasks include, but are not limited to: (1) nanoparticle ink synthesis, (2) mechanical/fixture design and assembly, (3) materials printing using electrospray and inkjet, (4) characterization of deposit structure using microscopy, and (5) data analysis and interpretation. Strong theoretical background in fluid dynamics, interfacial phenomena, and colloids self-assembly is highly desirable. Experience in atomization, materials printing, and/or microscopy is an advantage. The position provides an annual stipend and full tuition support. Applicants should contact Dr. Xin Yong (email@example.com) or Dr. Paul Chiarot (firstname.lastname@example.org) for more information. This position is contingent on acceptance into the Graduate School at SUNY Binghamton.
2. Funded PhD Position in Materials Science and Engineering
A funded position is available for a new PhD student in Materials Science and Engineering at the State University of New York (SUNY) at Binghamton. We are looking for enthusiastic and capable students to carry out analytical and computational studies on the behavior of complex fluids and polymeric materials. In particular, the current focus of the group encompasses modeling the following phenomena: interfacial self-assembly of stimuli-responsive nanoparticles, electrospray of colloidal inks, droplet impact on soft surfaces, flow of multi-phase fluids in confined geometries, and behavior of functional polymer nanocomposites. The ideal candidate should have extensive C/C++ coding experience. Knowledge of either statistical mechanics, fluid dynamics, interfacial phenomena or polymer physics is desirable. A background in Unix/Linux, parallel computing, and specific simulation techniques (molecular simulations, dissipative particle dynamics, or lattice Boltzmann method) is an advantage. Applicants should contact Dr. Xin Yong (email@example.com) for more information. This position is contingent on acceptance into the Graduate School at SUNY Binghamton.