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The goal of this project (“Digital fabrication of functional gradient materials aided by artificial intelligence methods: a step towards next-generation porous materials” NCN Opus 19, 2020/37/B/ST8/02167) is the development of new tools for the design and manufacturing of 3D porous functionally graded materials (pFGMs) that exhibit tailored mechanical properties, in particular pre-designed energy absorption profiles. The ability of controlling the energy absorption of graded materials is of critical importance in a vast range of industrial applications that span from aerospace and construction to transportation and bioengineering. However, due to the intrinsic complexity of pFGMs and the lack of a comprehensive model for such material design, researchers working in the field have limited possibilities and often prefer to proceed with empirical trial-and-error approaches. Here, we propose a new approach towards the design and fabrication of pFGM aimed at i) developing efficient in silico (numerical) modeling of such complex materials enabling the design of porous structures with required mechanical properties, and ii) simplifying / extending the manufacturing procedures.

To support the principal investigator in setting up the digital manufacturing platform and in manufacturing the FGMs. In particular, the Post-doc should process the data obtained from in silico simulations into inputs processable by the 3D printer (i.e. generate custom g-codes for the simultaneous control of the microfluidic printing head and of the robotic motion).

• 14.5-months full time work contract
• Work in the outstanding scientific institution in the dynamic research group of Digital Manufacturing of biomimetic systems
• Engagement in an ambitious research program and possibility to build the academic career
• International collaboration with leading Universities

• Participation in Erasmus projects

• PhD degree in engineering, materials science, chemistry or related fields obtained not earlier than 7 years before the engagement in the project (this period might be longer due to family reasons according to NCN rules).
• Experience in microfluidics, porous materials synthesis, image processing, machine learning will be an asset
• Knowledge of basic techniques and protocols used in chemistry lab
• Proficiency in spoken and written English

The Commission will take into account the following criteria:

• Competence for specific tasks in a research project
• Previous scientific achievements (publication record, H-index etc.)
• References
• Candidate’s own initiative in research projects