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. Creation of new functionalities: Design and implement new modules in both backend and frontend under the supervision of the senior team. Code quality (QA): Perform unit and integration testing to ensure
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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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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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properties of high-entropy alloy (HEA) nanoparticles. The SIESTA code will be used to compute key descriptors such as formation energies, mixing enthalpies, adsorption energies, d-band centers, and work
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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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/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