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Postdoc/PhD on inverse design of functional mate ... (No replies)
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Within the research group Theory of Magnetic Materials (https://www.mawi.tu-darmstadt.de/tmm) of the Institute of Materials Science,
we are seeking applications for one Postdoc/PhD positions [m/f/d] working on inverse design of functional materials in collaboration with Prof. Hongbin Zhang (TU Darmstadt) starting summer 2023.
Machine learning has been widely applied to obtain statistical understanding and rational design of advanced materials by mapping out the composition-processing-(micro-)structure-property relationships. The concept of inverse design can be implemented and carried out in three different flavours, i.e., high-throughput combinatorial computation [1], Bayesian optimization [2] and adaptive design [3], and generative deep learning [4].
We are looking for excellent candidates in this direction on functional materials, fulfilling the following requirements:
The Technische Universität Darmstadt is internationally oriented and committed to excellence. Foreign applicants are explicitly invited to apply. The University offers generous terms and conditions of employment, a wide range of benefits, services, facilities and family friendly policies.The Technische Universität Darmstadt intends to increase the number of female employees and encourages female candidates to apply. In case of equal qualifications applicants with a degree of disability of at least 50 or equal will be given preference. Wages and salaries are according to the collective agreements on salary scales, which apply to the Technische Universität Darmstadt (TV-TU Darmstadt).
Please address your application with the documents (CV, certificates, publication list, names of 3 references), preferentially as one PDF file by email to Hongbin Zhang ([email protected]), Technische Universität Darmstadt, Material Science, Research Group Theory of Magnetic Materials, Otto-Berndt-Str.3, 64287 Darmstadt, Tel.: 06151/16 23135.
[1] Topical review “High-throughput design of magnetic materials” https://doi.org/10.1088/2516-1075/abbb25
[2] Y. Zhang, et al., arXiv:2203.07892 https://arxiv.org/abs/2203.07892
[3] Z. Rao, et al., Science 378, 78 (2022) https://www.science.org/doi/10.1126/science.abo4940
[4] CCDCGAN: Inverse design of crystal structures Acta Mat. 231, 117898 (2022) https://doi.org/10.1016/j.actamat.2022.117898