Postdoc in the field of Materials Science and Engineering - Linköping University

Work assignments 

Subject area: Computational studies of the influence of microstructural features on the structural integrity of metallic materials using machine learning

Subject area description: Structural integrity of materials is of primary concern in sustainable mechanical design, as more durable products impose longer product lives and allow the usage of less material. Accounting for structural integrity in the design process calls for a technical model of the product concept, i.e., mathematical models of the product and its in-service environment, which inevitably must incorporate the influence of the material and its properties. This research position focuses on computational approaches to assess the influence of the material microstructure on structural integrity, incorporated in technical models intended support design decisions related to manufacturing and process parameter selections; known to influence the material microstructure.

Duties: The post doc will develop and apply computational methods incorporating machine learning to predict the influence of microstructural features on the structural integrity of metallic materials, e.g., resistance to plastic deformation and crack growth. Responsibilities include the design and implementation of finite element multiscale models and machine learning algorithms, analyzing related experimental data, and collaborating with industrial collaborators to validate computational predictions. The post doc may also contribute to manuscript preparation, present findings at scientific conferences, and mentor junior team members as part of an interdisciplinary research group.

The work is performed in connection to two ongoing research projects “Probabilistic multiscale modelling of the macroscopic crack growth behavior in heterogeneous materials” and “Optimized Digitalization for Environmentally NeutrAl Industrialization”, involving both academic and industrial partner.

As postdoc, you will principally carry out research. A certain amount of teaching may be part of your duties, up to a maximum of 20% of working hours., e.g., lab assistance, exam correction, classroom teaching, student supervision etc.

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