PhD position on theory and computational design of functional oxides

Reference : MRT-2019-029

Type: PhD Student
Contract type: Fixed term contract
Duration: 14 months (+ 22 months + potentially 12 months extension)
Place: Belvaux



As a key player in research and innovation in Luxembourg, the Luxembourg Institute of Science and Technology (LIST), with its employees, is active in the domains of materials, the environment and IT. As an RTO (Research and Technology Organisation) and with its interdisciplinary impact-driven approach, LIST contributes to the development of Luxembourg’s economy and society.
The Materials Research and Technology Department (MRT) translates cutting-edge materials research into applicable technology, with about 150 collaborators. For this, the department cultivates close relationships and joint projects with both academic and industrial partners, and contributes to Luxembourg's and Europe's innovation agenda in Materials Research and Technology.




The goal of this thesis is to understand the nature and properties of “domain liquid” states as those observed in heterostructures formed by perovskite oxides PbTiO3 (ferroelectric) and SrTiO3 (ferroelastic), which display spontaneous drifting of ferroelectric domain walls [Zubko et al., Nature 534, 524 (2016)]. Work will be based on novel “second-principles” simulation methods that provide an unprecedented level of atomistic detail and quantitative accuracy, while being computationally tractable. We will determine the conditions permitting the thermally-activated motion of ferroelectric walls in PbTiO3/SrTiO3 compounds, and identify other ferroelectric or ferroelastic materials in which similar effects may occur and be optimized. We will characterize the functional properties of such “domain liquid” states, and estimate their potential use in various applications.





  • Masters degree in condensed-matter physics, physics, quantum chemistry, materials science, mathematics, or related area
  • Excellent academic record


  • Strong taste for theoretical and simulation work. Familiarity with at least one language for scientific coding (python, fortran, C++) is an asset


  • Fluent in English (both spoken and written)


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 Stéphanie LUCADELLO

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