We are seeking a full-time Postdoctoral Research Assistant in Machine Learning based Computational Mechanics to join Antoine Jerusalem's Group at the Department of Engineering Science (central Oxford). The post is funded by EPSRC and is fixed-term for 1 year with the possibility of an extension.
You will be involved in the Prosperity Partnership for Advanced Simulation and Modelling of Virtual Systems (ASiMoV) and, in particular, the task called Disruptive approach: AI-based upscaling in collaboration with Professor Pena, Lurtis Ltd., an SME based in Oxford and specialised on machine learning and Rolls-Royce. This task will make use of the recently developed Soft Finite Element Method for geometry and material property optimisation for Rolls-Royce applications.
The candidate will collaborate tightly with Rolls-Royce to specialise the algorithm to applications of interest to Rolls-Royce, while further developing the approach.
You will hold a relevant PhD/DPhil (or be near completion) with relevant experience and have established knowledge/expertise in machine learning and programming and computational mechanics. Experience in Python and C++ and contributing to publications and presentations is also required.
Informal enquiries may be addressed to Antoine Jerusalem at this email firstname.lastname@example.org.
Only online applications received before midday on 23rd August 2021 can be considered. You will be required to upload a covering letter/supporting statement, including a brief statement of research interests (describing how past experience and future plans fit with the advertised position), CV and the details of two referees as part of your online application.
The Department holds an Athena Swan Bronze award, highlighting its commitment to promoting women in Science, Engineering and Technology.
Keywords: Finite element, machine learning, programming