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Field
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-checked security guarantees. In parallel, we will investigate how modern AI techniques can accelerate large-scale formal verification, developing AI proof agents that can maintain, extend and refactor
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have: A PhD in electrical engineering, energy engineering, mechanical engineering, control engineering, operations research, applied mathematics, or a closely related field. Documented experience in
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more efficient use of energy. Approximately 25 colleagues work at the division, including 15 PhD students. On the international level we collaborate with universities and institutes in Europe, Asia, and
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the content of the science they study. You will be an active member of RCNP. You will collaborate with the other postdoctoral researchers, PhD candidates and senior investigators, participate in seminars and
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have completed a PhD (submitted and defended) by the application deadline. Artists who hold a doctorate and have experience in academic collaboration are also encouraged to apply for an academic
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research. Preferred Qualifications: Candidate should have a PhD in Solid Mechanics specialization. Experience with nonlinear elasticity, finite deformation mechanics, continuum mechanics, finite element
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. Job Requirements: PhD in Geophysics, Seismology, Civil/Structural Engineering, Engineering Mechanics, Applied Physics, Electrical/Computer Engineering, or a related field. Strong research record in
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Employment 1.0 FTE Gross monthly salary € 3,706 - € 5,760 Required background PhD Organizational unit Faculty of Science Application deadline 14 October 2026 Apply now Join an ambitious
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systems. In parallel, they will design and develop agentic AI and physics-aware AI models to accelerate discovery and deepen mechanistic insight in catalysis. This work will be carried out in close
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cell lysis, restricting analysis to single timepoints and necessitating parallel samples. This prevents temporal tracking in the same cells and poses challenges for scarce primary samples. The use