This project is part of our joint efforts with NCCR MARVEL (https://nccr-
marvel.ch/people/projects/novel-materials) in the computational design of new 
advanced materials for laser 3D printing applications. At the same time in LAMP, 
we apply extensive expertise in process design, monitoring, and control as well 
as state-of-the-art multiphysics modeling and machine learning techniques 
towards designing Digital Twins for Laser Metal 3D printers, significantly 
reducing the trial-and-error experimental efforts in simultaneous process<-
>material optimization (https://www.empa.ch/web/s204/modeling-simulations). 
Specifically for this project, we are using Beam 3D printers 
(https://www.youtube.com/c/beammachines) with our world-unique setup of 
simultaneous injection of metal powder and reinforcement nanoparticles, which 
allows for local modification and fine-tuning of process-microstructure-property 
relations during laser metal deposition (https://www.mdpi.com/1996-
1944/12/21/3584). Thus, multiscale multiphysics modeling approach accelerated by 
deep learning and supported by benchmark and validation experiments is required 
for successful execution of this project. 
The research is multidisciplinary and requires close collaboration with 
experimentalists as well as multiphysics modeling and machine learning experts 
in the lab. We offer a world-class mentorship, an excellent infrastructure, and 
broad interdisciplinary surroundings with plenty of possibilities for personal 
and professional development. Due to a high world interest in additive 
manufacturing of metals and alloys, the research experience acquired in this 
program will guarantee exciting future opportunities both in academia and 
industry, nationally and internationally. The work will be carried out at Empa 
in Thun, next to Bern, Switzerland, and the resulting PhD degree will be issued 
by EPF Lausanne.
Your profile:
You hold a recent Master degree in computational physics, chemistry, materials 
science, mechanical engineering, applied mathematics, or a closely related field 
with outstanding grades. Good programming skills in C++ and Python and 
experience with version control systems and platforms are required for this 
position. Some experience with any of discrete element, computational fluid 
dynamics, phase field, molecular dynamics (OpenFOAM, LIGGGHTS, LAMMPS, 
FLUENT,etc.) as well as Bayesian inference and machine learning would be an 
advantage.
A strong desire to work at the leading edge of materials technology and a high 
level of motivation to work in an international, multidisciplinary research team 
in the field of materials science are essential. Good knowledge of English (oral 
and written) is mandatory. Knowledge of German or French would be an advantage. 
The full-time position is limited to 3 years with possibility of extension to 4 
years, and is available immediately or upon agreement.
For further information about the position please contact Dr. Vladyslav Turlo 
(vladyslav.turlo@empa.ch) and visit our websites https://www.empa.ch/web/s204.
We look forward to receiving your online application including a motivation 
letter, CV, diplomas with transcripts of records as well as the contact details 
of two referees. Please upload the requested documents through our webpage. 
Applications via email will not be considered.
https://apply.refline.ch/673276/1686/pub/1/index.html