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with Poleno Jupiter instruments, with data obtained with DNA methods and data obtained with a Hirst trap. • Numerical models used by the group covers the particle dispersion model HYSPLIT in
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Alternaria alternata and Phytophtora infestans You will work with data obtained with Poleno Jupiter instruments, with data obtained with DNA methods and data obtained with a Hirst trap. Numerical models
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physics and experience with quantum many-body scars is an advantage. Experience within numerical methods for quantum many-body systems is required. Personal and collaborative skills are also important
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as possible thereafter. The successful candidate will develop new theoretical frameworks and computational methods to investigate the fundamental limits of polariton-mediated inelastic electron
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are expected to have a solid background in quantum physics and experience with quantum many-body scars is an advantage. Experience within numerical methods for quantum many-body systems is required
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. This is a fixed-term position to end 24 months after the start date. Job description The postdoc position focuses on physics-driven machine learning methods for ground-based, airborne and drone-based
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numerical performance and interoperability. Extend the framework to include CCUS and PtX components (compressors, coolers, JT flash for CO₂ conditioning, storage tanks, pipeline transport
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and magnetism Experience with Fortran or high-performance numerical methods Experience with writing and publishing scientific articles. Ability to work independently, to plan and carry out complicated