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science. Electronic structure calculations (e.g. DFT or tight-binding methods), or thermodynamic modelling (e.g. statistical mechanics, MD or CALPHAD). Scientific data analysis. Interdisciplinary research
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that support both organizational objectives and employee needs. The position includes the collection and analysis of qualitative and quantitative data, publication of scientific findings in international
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dissemination of research results Operation, setup, and maintenance of laboratory equipment. Experimental data processing and analysis. Requirements: The successful candidate must hold a Ph.D. degree in Materials
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biology, AI guided protein engineering and chemical analysis, you will establish the molecular basis of REE binding and discrimination in naturally evolved lanthanophores, establishing the ‘rules’ of REE
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. Demonstrable experience with data processing, signal analysis and programming (e.g. Python/Matlab). Ability to work independently as well as in a multi-disciplinary team. Fluent in English (oral and written
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intelligent built environments, and analysis of behavioral and physiological data. The work also includes the development of personas, the use of LLM‑enhanced decision narratives, and agent-based social
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-centred design in vulnerable neighbourhoods. By combining qualitative and GIS-based mapping, community-oriented visual design engagement methods, and stakeholder analysis at multiple scales and in diverse
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system analysis . Rigorous formal methods will ensure that learnt machine learning methods and the resulting systems are indeed resilient, aiming at improved dependability and trustworthiness. Formal
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research results; • be able to use basic software for data analysis and documentation, such as MS Office, Origin and GraphPad Prism; • demonstrate accuracy, reliability and attention to the quality
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energy Risk analysis Life cycle assessment (LCA) and modeling Should one or two of these components be lacking, it is nonetheless possible to supplement the knowledge base after the admission. Great