Computational Materials Scientist: Multiscale modeling of hydrogen interaction with materials
To strengthen the materials science competence, ASML Research is looking for a computational materials scientist who can add value to the understanding of materials degradation in the operating environment.
You will work in a multidisciplinary team of Chemists, Physicists, Materials Scientists, Electrical and Mechanical Engineers.
You will bring multi-scale simulations into the big picture by ideating and developing multi-scale modeling workflows which combine multiple models bridging time- and length-scales (DFT, MD, CFD, FEM, FD), identifying the existing conceptual and methodological gaps required to develop these workflows, and proposing innovative solutions to move forward.
You have demonstrated experience with modeling of impurities in materials and in particular hydrogen-related diffusion and mechanical phenomena. Furthermore, you play a key role in implementing and supporting a state-of-the-art infrastructure for materials development.
Based on high-level problem descriptions you define hypotheses on underlying mechanisms governing the behaviors observed from experimental measurements, set up elaborate models to verify the validity of such hypotheses, provide fundamental understanding and translate the results of the simulations into thermodynamic and kinetic equations that can be used to describe the behavior of the system at the material and component level, thereby suggesting design rules to improve product performance.
Your job requires hands-on simulation/modeling of actual systems and problems with required software tools.
On the other hand, you have to proactively extend an existing network of commercial and academic partners to a chemistry and materials modeling ecosystem that guarantees the access of ASML to state-of-the-art developments and techniques in the field.
University PhD degree in Computational Materials Science/Multiscale Materials Modeling with a strong focus on materials mechanics, crystal plasticity, materials failure, embrittlement, mass transport and diffusion phenomena in materials, and coupling of thereof.
Ability to design original multiscale strategies by combining discrete and continuum methods bridging time- and length-scales, and implement them into functional modeling workflows give you a head start. Ideally, you also have experience with Materials Informatics and High-Throughput simulations.
Relevant experience of more than 7 years after PhD and a broad knowledge of various modeling techniques are essential.
Demonstrated experience in computational materials science and multiscale modeling of materials. Working knowledge in designing and performing computational simulations linking classical or quantum atomistic methods for the material simulation to higher-level continuum methods, to predict the impact of the microstructure on the meso- and macro-scale behavior at the material and component level.
Understanding of equilibrium thermodynamics and equations-of-states, and preferentially of advanced related topics such as non-equilibrium thermodynamics. Ideally you are familiar with the theory of activated complexes/transition state theory and chemical kinetics, and know how to perform model reduction to condense the complex results of the multiscale simulations into simple rate equations or models useful for the description of experiments in laboratory equipment and machines.
Broad knowledge in materials behavior and phase transformations and/or chemical kinetics at different time and length scales. Experience in running computational chemistry, or materials science software tools based on atomistic methods such as molecular dynamics, and in linking the calculated observables to higher-level computational models using finite elements or finite difference methods, the simulations of which are performed using either commercial or in-house software tools.
Understanding and modeling of mass transport behavior and associated thermomechanical stability of complex materials and composites against external stress factors such as temperature, chemical reactions, grain boundaries, interfaces, etc.
Knowledge of reactive and diffusion processes in materials and interfaces involving contaminants/impurities and gas phase species including radicals and ions. Basic knowledge on plasma processes is welcome.
Experience in modeling hydrogen diffusion and interaction in complex, highly-structured materials, and plasma-related chemistry gives you a head start.
Knowledge of machine learning/materials informatics is a plus.
Open to learning techniques outside of the above mentioned fields in the future.
Proactive and autonomous while driving to success in a highly skilled team of experts towards a common goal.
Pragmatic attitude with an analytical view.
Able to see the big picture and create a vision and have perseverance in realizing it.
Context of the position
The Research Materials Science andChemistry group is part of the Research department of ASML. This group identifies and fills in technological gaps in the future roadmap of lithography and the lithography market. Our focus is on advanced material research and on the interaction of light (13.5 nm) with the gaseous background in our tools and on solid materials. We work in small teams and deliver solutions that can be transferred to Development and Engineering. We work together with external research institutes and universities.
This position may require access to controlled technology, as defined in the Export Administration Regulations (15 C.F.R. §730, et seq.). Qualified candidates must be legally authorized to access such controlled technology prior to beginning work. Business demands may require ASML to proceed with candidates who are immediately eligible to access controlled technology.