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research ideas, and to have solid mathematical foundations, such as in linear algebra and relational algebra, to support the design and analysis of your algorithms. You should be curious, motivated, able
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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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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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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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theoretical knowledge, the ideal candidate should have experience with experimental work within material characterization and on compilation of large datasets and statistical analysis of these. In addition
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experience in fieldwork and data analysis to technically oriented candidates with expertise in AI and interactive systems development. Scientific dissemination is expected to focus on leading Human-Computer
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methods and theories. You can work independently while contributing actively to a collaborative and inclusive research environment. Experience working with quantitative data, statistical analysis, or survey
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electrical energy storage systems; energy management systems. Experience with data processing, statistical analysis and machine learning techniques is an advantage. Knowledge with Mathworks suite, C/C++ and
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to the user, which pictures to show? A third possible topic is performance improvement of using a graph-based analysis and/or infrastructure. Typical RAG systems use a semantic search based on embeddings. NEO
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and reshapes higher education practices over time. Methodologically, the project will adopt a mixed-methods design that may combine qualitative inquiry, comparative case analysis, and quantitative