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Field
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2: An MSc degree in electrical engineering, applied physics, or a closely related field, with strong experimental academic results. A solid foundation in electrical measurement, power electronics
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of blades to discs using solid-state joining is a key factor in achieving cost-effective, high performance and low-weight fan and compressor stages in aero-engines. LFW is an established joining process
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and other partners, will provide crucial experimental insights for designing safer and more reliable hydrogen-resistant circular steels. In this role, you will develop fundamental insights
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experiments. Documenting, reporting and presenting results to the research team. Collaborating with members of the experimental team to analyze the acquired data and process it using computational methods
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of blades to discs using solid-state joining is a key factor in achieving cost-effective, high performance and low-weight fan and compressor stages in aero-engines. LFW is an established joining process
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microstructure and structural performance. The outcome of this research, conducted in close collaboration with Tata Steel and other partners, will provide crucial experimental insights for designing safer and more
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prediction of machining results and improve process stability with fewer experimental iterations. The project integrates antibacterial coating strategies to predict coating efficacy and long-term surface
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graduate and undergraduate researchers, and help maintain shared instrumentation and safe laboratory practices. Required Qualifications Ph.D. in Chemistry, Physics, Materials Science, or a closely related
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, reproducible experimental procedures, and reusable physical-security testbeds. This will strengthen the HRE Lab as a sustainable experimental platform for advanced hardware security research, future PhD and
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AITHYRA GmbH - Research Institute for Biomedical Artificial Intelligence of the Austrian Academy of Sciences | Vienna, Virginia | United States | about 11 hours ago
co-pilot throughout the entire scientific process - from hypothesis generation and experimental design to biological interpretation and therapeutic innovation. Through a coherent integration of AI/ML