Research Associate (m/f/d) in the field of Materials Science and Sustainable Metallurgy
Leibniz-Institut für Werkstofforientierte Technologien - IWT
What you can expect from us:
- remuneration based on the federal collective bargaining agreement (TV-L), pay group 13 (from EUR 4,760 per month full-time), annual bonus, company pension scheme
- support for personal further qualification as part of a doctorate (Dr.-Ing.) in cooperation with the University of Bremen
- family-friendly, flexible working time models, part-time option, remote work, additional days off on December 24 and 31
- corporate health management and sports activities through egym wellpass
- Interdisciplinary and international environment
- project work with focused on advanced metallic materials, incl. integrating cutting-edge AI tools to accelerate material design, in cooperation with German and International (e.g. Japan, South Korea) partners
- operate state-of-the-art research infrastructure, such as additive manufacturing machines, sintering device, liquid metal dealloying equipment, atomization plants
- analyze synthesized materials using a suite of analytical methods, such as scanning and transmission electron microscopy (SEM/TEM), Electron Backscatter Diffraction (EBSD), and X-ray diffraction (XRD)
- present research findings international conferences and publish peer-reviewed papers in high-impact scientific journals
- contribute to the preparation and acquisition of third-party funded research proposals
- completed Master's or Diploma degree in materials science, physics, mechanical engineering, physical Metallurgy or a comparable engineering / natural science discipline
- practical experience in a laboratory environment utilizing advanced synthesis methods (e.g., additive manufacturing, sintering, dealloying).
- expereince in Materials Science, Physical Metallurgy and Thermodynamics
- experience with analytical characterization techniques, including SEM/EDX, EBSD, XRD, and mechanical testing
- Initial experience with, or willingness to learn and apply, computational simulation methods (such as FEM, Thermo-Calc, and CALPHAD) alongside AI tools in materials science
- fluent in written and spoken English (B2), with ability to work systematically and on complex research topics
Please send your application including a cover letter, CV and graduation certificates until 29.07.2026, quoting the reference number V 26-2.