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to the body of knowledge by enhancing the safety, relia- bility, and efficiency of automated vehicles by developing a collaborative multimodal perception system. This system leverages data from multiple sources
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from on-board and off-board sensors have been collected and analysed. However, such raw data collected from multiple sensors is often disturbed and does not indicate the ship performance at calm water
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-mediated services for stakeholders Strategic alignment of AI with service design and business strategies and models Responsible management The candidate will conduct interdisciplinary, mixed-methods research
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for functional safety and security, and introducing DT-based verification methodologies, including the generation of virtual safety cases aligned with ISO 26262 and SOTIF standards. Implementation and case studies
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environment aligns with the Estonian smart specialization growth area “ICT horizontally through other sectors.” Specific aim and scientific approach The aim is to enable PEB and PED through innovative
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to developing a quantitative decision support system for environmental, social and health impact assessment (ESHIA) aligned with the targets of the UN Sustainable Development Goals (SDGs). Implementation
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and policy decisions based on an environmental, social and health impact assessment (ESHIA) methods aligned with the targets of the UN Sustainable Development Goals (SDGs). Implementation
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environment for PhD students interested in electronics and communication technologies. Research Focus: The department specializes in Cognitive Electronics and Communication Technologies, aligning its research
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combine high-level research with the development of innovative solutions to promote a sustainable mindset and practices. By integrating expertise from multiple disciplines and fostering international