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widely used by the academic community (about one thousand citations per year), and has been a flagship code of the MaX European Centre of Excellence for exascale computing in Materials Science (www.max
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of Group/Project: We are building an optimisation-driven framework that makes AI models reliably operate advanced scientific software (e.g., DFT, Wannierisation, and quantum-transport codes) and (ii) uses
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widely used by the academic community (about one thousand citations per year), and has been a flagship code of the MaX European Centre of Excellence for exascale computing in Materials Science (www.max
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Calculations will be valued but it is not essential. · Previous knowledge of Density Functional Theory (DFT) and experience with DFT codes will be very highly valued. · Knowledge of chemical reactions and how
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Computing. · Experience with High Throughput Calculations will be valued but it is not essential. · Previous knowledge of Density Functional Theory (DFT) and experience with DFT codes will be very highly
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/Project: We are building an optimisation-driven framework that (i) makes AI agents reliably operate advanced scientific software (e.g., DFT, Wannierisation, and quantum-transport codes) and (ii) uses
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/Project: We are building an optimisation-driven framework that (i) makes AI agents reliably operate advanced scientific software (e.g., DFT, Wannierisation, and quantum-transport codes) and (ii) uses
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(DFT) packages and in-house quantum transport codes. Fully converged simulations from established databases will serve as ground-truth benchmarks. In parallel, the same optimisation principles will be
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Finesse, SIS, and others; knowledge of commercial codes like Zemax are a plus. Experience with electronics or hardware development, or commissioning of gravitational-wave detectors, is desirable. Good
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The successful candidate is expected to have: PhD Physics Internationally recognized experience on research using the LIGO-Virgo data Experience developing pipelines and code for gravitational-wave searches and/or