We are looking for a postdoctoral computational scientist/applied mathematician to join the Chair of Computational Mathematics and Simulation Science, lead by Prof Jan S Hesthaven, to work in the area of scientific machine learning.
Current activities focus on the development of collaborative modes of interaction between modern computational methods and recent machine learning techniques, in particular based on neural networks. Such developments seek to overcome known algorithmic bottlenecks or enable entirely new ways of solving problems of relevance to science and engineering. The postdoctoral fellow is expected to engage in different projects in line with the above vision.
The ideal candidate will have the following skills: A PhD in mathematics, mechanical engineering or related topics; Experience with model order reduction techniques; Experience with modern computational methods for solving PDEs; Good programming skills.
The effort is of a collaborative nature so strong interpersonal and communication skills are required. Working language is English. There will be some teaching responsibilities at EPFL as part of the position.
We offer a 1 year contract with the possibility of an extension, a dynamic and inspiring working environment, and a competitive salary. A start date of January 1, 2021 is preferred but this is negotiable.
To express your interest, please send a letter of motivation, a resume, and at least 2 names of references to mcss@epfl.ch. Evaluation of applications will begin late September and continue until the position is filled.
}, issn = {}, doi = {https://doi.org/2021-CAM-19586}, url = {https://global-sci.com/article/75454/postdoc-position-scientific-machine-learning-epfl-ch} }