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experience with Open Science practices (e.g. contributions to open-source libraries, research data repositories) Personal attributes Strong communication skills for interdisciplinary collaboration Ability
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, fitting to the project plan. Your profile The candidate should have a PhD degree in natural resource economics or a similar subject. Proven experience in data analysis of markets related to natural
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mathematical modeling of infectious diseases applied to grided spatiotemporal data inputs. The project involves reviewing existing literature and especially synthesize model structures and parameters for the eco
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sequencing and synthesis to design useful cell behaviors. The scope of this project is to combine multi-gene control technology and computer algorithms to develop a foundational discovery platform for future
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Worldwide R&D Projects. Previous experience in one or preferably more topics from these areas is considered a merit: -Multi-modal data processing for decision-making in natural environments -Terrain
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information see https://portal.research.lu.se/en/persons/vasili-hauryliuk. Work duties and responsibilities The tasks as a postdoctoral researcher mainly involve conducting research. Teaching may be part of
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experimental and computational tools, and are currently recruiting for the following roles: Position 1: AI and data science approaches applied to genomics and spatial omics Position 2: Experimental islet and
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test planning, instrumentation (e.g., strain gauges, LVDTs, DIC), execution of large-scale tests, and data analysis. Solid understanding of structural behavior, failure mechanisms, and durability issues
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digital twin framework, adaptable to: The level of detail available for ship modelling, The quality of risk-related data, and Quantified model and data uncertainties. The project will advance knowledge
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. Strategic management of platforms and innovation ecosystems – open innovation, platform orchestration, and multi-stakeholder partnerships in dynamic environments Strategic use of intellectual assets and data