Digital methods for inverse materials design are essential to efficiently create new, sustainable and recycling-adapted structural metals. Alloys with a reduced number of elements, so-called lean alloys, and material systems with a high tolerance to impurities from the use of secondary raw materials are of particular relevance for improving recyclability and sustainability. Al-Ca is a promising lean alloy system for additive manufacturing, as the mechanical properties can be tailored through phase composition, distribution and morphology by tuning process parameters. The work is carried out within the DFG Priority Programme “DaMic - Data-driven Alloy and Microstructure Design of Sustainable Structural Metals” (SPP 2489), in close collaboration with a research partner responsible for the manufacturing and characterization of material samples.
Your Tasks:
- to develop automated workflows for descriptor based microstructure reconstruction
- to identify material parameters for crystal plasticity simulations from experimental data through inverse analysis
- to establish structure–property linkages based on numerical simulations and to transform them into AI- and ML-ready information
- to develop and implement an indirect inverse optimization framework to identify microstructures that exhibit desired macroscopic properties
- to publish and present research results in relevant journals and at international conferences
Table of Content
Summary
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Benefits
- The opportunity to conduct exciting research in an international and multidisciplinary environment with outstanding infrastructure
- A creative work environment at a leading research facility, located on an attractive research campus at the TZA Aachen https://tza-aachen.de and the Forschungszentrum Jülich
- The opportunity to gain your reputation in a dynamic and highly active research field
- Part-time position with 19,5 hours per week and flexible working hours
- 30 days of annual leave (depending on agreed working time arrangements)
- Further development of your personal strengths, e.g. through an extensive range of training courses; a structured program of continuing education and networking opportunities specifically for doctoral researchers via JuDocS, the Jülich Center for Doctoral Researchers and Supervisors: https://www.fz-juelich.de/en/judocs
- Targeted services for international employees, e.g. through our International Advisory Service
Requirements
- A completed university degree (Master or equivalent) with excellent grades in the field of mechanical engineering, material science, physics, computational science or similar, with experience in modeling and simulation
- Strong understanding of the (computational) mechanics of solids and the finite element method and/or spectral solvers
- Practical experience in at least one programming language (preferably Python) and experience with the use of Unix/Linux operating systems
- Structured and analytical thinking as well as a systematic, careful, independent, and reliable working method
- Interest in working closely with experimentalists
- Strong cooperation and communication skills and the ability to work as part of a team
- Excellent written and spoken English skills
Application Deadline
Not SpecifiedHow To Apply
Are you qualified and interested in this opportunity? Kindly go to
Forschungszentrum Jülich on www.fz-juelich.de to apply
For more information, kidny visit FZ Julich scholarship webpage.
