Position description
We are looking for a skilled postdoctoral researcher in materials computational sciences with expertise in the multiscale modeling of materials for energy applications. Strong background in physics, material sciences and computational modeling is needed. Skills in programming and the use of machine learning techniques are a bonus.
The postdoc will work at the university of mons that is coordinating the EU M-ERANET project ‘PHANTASTIC’
PHANTASTIC aims at providing a multiscale materials computational sciences engineering approach combining data- and physics-driven models for the design of multi-layered lead halide perovskites with improved stability. The materials engineering approach that will be applied relies on the interfacing of 3D lead halide perovskites to properly designed 2D lead halide counterparts. The large chemical space will be explored by training Machine Learning (ML) algorithms against state-of-the-art ab initio molecular dynamics and electronic structure calculations. These will be used in the implementation of a numerical solver coupled with drift-diffusion Poisson equations and the results compared to experimental data provided by advanced experimental characterization tools. A special focus will be devoted to structural rearrangements with time and exposure to environmental factors and light irradiation of 2D, (quasi)2D, 3D lead halide perovskites and their vertical heterostructures.
Deadline:
31 Aug 2022
Apply:
Interested candidates can send their CV, cover letter and research proposal to
[email protected]
Related articles:
