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integrated with bioinformatic analysis to examine how chromatin states change during development and identify regulatory principles shared across, or specific to, different neural lineages. The student
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. Applicants should have an academic background in a field such as sustainability science, economics, finance, geography, environmental science, systems analysis, or related disciplines. Please note that both
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technologies; Secure protocols and cryptographic mechanisms for intelligent and distributed systems; Security analytics based on graph learning and large-scale data analysis. The research will
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Svalbard. Quality-controlled versions of all data are already available, so analysis can begin at the project start.The PhD student will develop a detailed understanding of aircraft instrumentation
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contribute to co-creation of knowledge. The project work will include quantitative analyses of data from registers, surveys and cohort studies as well as qualitative analysis of data collected through
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systems, wearable-data analysis, environmental monitoring, and decision-support systems for assisted and autonomous driving. The project is part of a vibrant academic community with a strong
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, mathematical analysis, or applications in areas such as healthcare, autonomous systems, and cyber-physical systems. The project welcomes applicants from machine learning, computer science, mathematics
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. Data analysis requires quantitative approaches, including statistical analysis and modelling to interpret the data. There are opportunities to collaborate with national and international research
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the research project to which the employment is linked (where applicable) independence in the analysis and planning of previous scholarly work scholarly stringency and quality of previous work and of
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interpretability. The proposed project focuses on developing AI strategies for the analysis of complex biological datasets, with a particular emphasis on microscopy. The PhD candidate will explore how