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for the position. Preferred selection criteria Competence in the theory of superconductivity, quantum transport and/or quantum information/cavity physics will be advantageous. Competence in numerical modelling will
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project in consultation with the PI. Conduct ethnographic fieldwork and contribute to developing new methods to advance project aims. Collect, analyse, visualise and interpret data through literature
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for critical applications and associated methods to assess performance and ensure stability in such high-risk AI systems.The group works in close collaboration with industry and national and international
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language skills Experience in the following will also count in the assessment of the applicants: computational and statistical methods for analysis; rodent behavioural assays, brain sectioning and
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quantum information/cavity physics will be advantageous. Competence in numerical modelling will be needed. Personal characteristics We are seeking a candidate who is independent, takes initiative and excels
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reliability of the applied methods; iii) explore how this training can be elaborated including simulation technology to support training outcome. The basis should be to further develop a training program based
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multispectral data, applying ML methods (e.g. XGBoost, LSTM, CNN). Run virtual “what-if” scenarios for nutrient, water, and light inputs to predict biomass, canopy, protein content and chlorophyll dynamics
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that will support educational stakeholders to interrogate and challenge vendors of AI based systems and products Robust methods for developing games and web services that can be used to support parents
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to interrogate and challenge vendors of AI based systems and products Robust methods for developing games and web services that can be used to support parents, teachers and students to understand and compare
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methods for developing games and web services that can be used to support parents, teachers and students to understand and compare different AI systems and services Decision support services to help