University of Freiburg 2025 PhD Candidate (m/f/d)

Digital methods for data-driven inverse materials design by optimizing composition process-structure-property relationships for aluminum alloys based on semantic data management technologies, physic-based modelling, and correlative microscopy

A high recycling rate while maintaining functionality is an important contribution to increasing sustainability in materials processing. In the case of aluminum, the reasons for this is that primary production (45 kWh/kg for the synthesis of aluminum form ores) consumes significantly more energy than the secondary route (the energy needed to melt aluminum from scrap is with 2.8 kWh/kg about 5% of the energy for ore reduction). In addition, the secondary route reduces the environmentally harmful mining and related social implications.

However, the challenges of (i) dealing with impurities remain (e.g., from coatings or from scrap mixtures) or undesirable accompanying elements and (ii) developing alloys like lean alloys in such a way that their recyclability is improved. This in-turn, leads to challenges in producing high-quality alloys and, unfortunately, often results in the preference for primary routes in industry. Moreover, aluminum itself and the often-used alloying elements like Mg, Si, Nb, Ti, Cu, Ni, etc. are listed as critical raw materials in 2023. Notably, alloying elements like manganese and chromium are sourced from only a limited number of regions globally; others, such as silicon, are costly to extract from silicon dioxide (SiO2).

The proposed project addresses the experimental investigation, modelling, and optimization of composition-process-structure-property (CPSP) relationships in the manufacturing of aluminum alloys. Here a special attention will be paid to the atom probe tomography experiments, which will be used in a correlative manner, i.e. together with the backscatter electron.

The INATECH group “Cross-scale material Characterization” possesses great experience in material characterization and will represent a unique expertise for the entire Consortium. Moreover, this experimental work will be put in conjunction with the simulations done at Fraunhofer IWM.

Summary

1. Application Deadline: August 31, 2025
2. Country to Study: Germany
3. School to Study: University of Freiburg
4. Study Level: PhD
5. Sponsor: University of Freiburg
6. Gender: Open to men and women
7. Duration: 3 years (with possible 1-year extension)

Eligibility Criteria for University of Freiburg 2025 PhD Candidate (m/f/d)

1. This position is limited to three years with the possibility of extension for a further year. The salary will be determined in accordance with E13 TV-L.
2. We will be particularly pleased to receive applications from women for the position advertised here.

Benefits of University of Freiburg 2025 PhD Candidate (m/f/d)

1. Salary based on E13 TV-L scale
2. Research and development support
3. Collaboration with Fraunhofer IWM
4. Advanced training in material characterization and simulations

How to Apply

Please send your CV, motivation letter, and grade transcripts to oana.cojocaru-miredin@inatech.de.

Please send your application, including supporting documents mentioned above citing the reference number 00004428, by 31. August 2025 at the latest. Please send your application to the following address in written or electronic form:

Albert-Ludwigs-Universität

INATECH

Prof. f. Skalenübergreifende Materialcharakterisierung

Prof. Dr. Oana Cojocaru-Mirédin

Georges-Köhler-Allee 102

79110 Freiburg

For enquiries, please contact Frau Prof. Dr. Oana-Eugenia Cojocaru-Miredin on the phone number +49 761 203-67637 or E-Mail oana.cojocaru-miredin@mail.inatech.uni-freiburg.de.

For more information, kindly visit University of Freiburg scholarship webpage.

Application Deadline

August 31, 2025

Application Link(s)

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