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Field
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as a change in how firms codify knowledge: prompts, models, workflows, and governance routines make some expertise executable while creating new burdens of evaluation, maintenance, and revision
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Arabidopsis thaliana or a comparable model plant system. Very good written and oral English language skills. Meriting qualifications The following qualifications are not required at the point of appointment
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simulation techniques, including density functional theory (DFT), molecular dynamics, Monte Carlo methods, and free‑energy perturbation calculations. Develop and implement novel computational methodologies and
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or heterogeneous environmental datasets Familiarity with spatial analysis, GIS, or geospatial data workflows. Experience with machine learning, modelling, or systems analysis approaches Interest in resilience
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and digital transitions, often referred to as the twin transitions. Across Europe, governments, industries and public institutions increasingly rely on scenarios, models, indicators, roadmaps and
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strong interest in e-health and digital health services, AI including large language models, and interdisciplinary work. The doctoral studentship forms part of Samverkan e-hälsa , a long-term collaboration
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Experience with multi-physics simulation, reliability and lifetime modelling is considered an advantage Knowledge of manufacturing and integration processes such as metallization, bonding, PCB fabrication
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characterization of HIV RNA/DNA in primary material as well as model cells using Oxford Nanopore sequencing and complementary molecular and computational approaches. The doctoral student will help develop, optimize
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on AI-empowered asset management using drone inspections and available asset management historical data. The aim is to enhance the asset and network resilience of ports by training an AI model on ferry
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research program focused on advanced neuroimaging and computational modeling in collaboration with Pediatric Neurosurgery and the Adult Cerebrovascular Division. This faculty member will develop a