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directions. In the first, you will work with market-driven optimal dispatch of coupled electricity–cooling systems. This includes: Modelling, analysis, and optimization of flexible cooling assets and
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for large-scale immunological and proteomic studies (e.g., Olink, MSD, etc). Lead data analysis and integration of omics datasets, contributing to scientific manuscripts and grant proposals. Provide
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, reviewing of literature, experimental work, modelling, data analysis, writing etc. The project can to some extent be tailored to the candidate’s interests and expertise. The PhD student will follow courses
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connecting empirical and conceptual insights across cases and levels of analysis, contributing to and strengthening the overall research agenda on sustainable human–robot collaboration in healthcare. You can
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year before the position expires, you will be offered an interview to clarify your future career. The PhD research will focus on the development of AI models for analysis of prehospital ECGs, with
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laboratory experiments. The candidate will participate in all aspects of the project including acquisition of data from the literature, experimental work, modelling, data analysis, writing etc. The project can
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. This may include interviews, participatory observations, document analysis, and involvement in co-creation and evaluation activities within school-based living labs. The PhD fellow will also contribute
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the high cost of representing large datasets in a form suitable for quantum computing, calling for a cost-benefit analysis of quantum machine learning algorithms. To address scalability for large datasets
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-ranking journals within the domains of Industrial Ecology, Sustainability Science, and Environmental Systems Analysis. Advance methodological development in LCA, including harmonization, modelling
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methods such as interviews, document analysis, case studies, and stakeholder workshops Be open to collaborate with practitioners and contribute to both academic and practice-oriented outputs Publish in