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Field
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while also offering scalability to dynamic and complex environments. The PDRA will also lead in-field testing and deployments. Therefore, we require someone with excellent implementation skills and
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, defensive mechanisms and related topics to the safe deployment of systems contain multiple LLM and VLM powered models. You will be responsible for Developing and implementing; capability evaluations, attacks
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modelling, advanced AI algorithms, and decision-support tool development for various hydrogen technologies-based energy systems. Responsibilities will include programming, analysing and interpreting data, and
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in peer-reviewed journals IT skills (e.g.- programming skills) Knowledge in Computational Medicinal Chemistry, Chemoinformatics, and Molecular Modeling Excellent knowledge of English (C1) Team player
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to apply social science research methods to area studies, moving beyond traditional linguistic-cultural approaches while avoiding purely universalist, theory-driven models of explanation, A completed Ph.D
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systems modelling including technical knowledge (e.g., in data science, input-output modelling, applied economic modelling, environmental and ecological assessments, GIS, comparative risk assessments), as
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executing research programmes related to different aspects of thymus biology employing informative experimental models and a broad range of analytical platforms, including single cell transcriptomic analysis
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systems modelling including technical knowledge (e.g., in data science, input-output modelling, applied economic modelling, environmental and ecological assessments, GIS, comparative risk assessments), as
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this, the Fellow will implement a universal design methodology for such fluids of complex rheology, using a Machine Learning (ML) algorithm to be incorporated in a Computational Fluid Dynamics framework. Training
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Association, NEBOSH). Proven experience in completing detailed Fire Risk Assessments and reports. Excellent communication and interpersonal skills, both written and verbal, with the ability to convey complex