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Seed project: Machine learning stabilized steady-state advective-diffusive heat transport This seed project aims to explore and use the strengths of Scientific Machine Learning (SciML) to solve the…
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Doctoral project: AI in administration of agricultural subsidies We want to design, implement and evaluate systems based on artificial intelligence that supports our customer with the administration…
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Project: VCardiac - A Novel Framework for Contactless Detection and Forecasting of Early Stages of Heart Diseases and Cardiac Arrest Conditions VCardiac is a new framework that utilises acoustic heart…
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Seed project: Programming social robots - a tool for learning in the multilingual primary school The aim is to contribute to teachers' capacity to work with programming social robots in classrooms…
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Project: Visualization and Exploration Flexiboard for Timber Buildings (TimberVis) Within the collaboration between InfraVis, the national research infrastructure for data visualization, and the…
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Seed project: Biosensor Testbed at the IoT Lab The objective of this project is to explore the potential applications of biosensors for the continuous monitoring and management of various health…
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Doctoral project: Enhancing MLOps architectures for efficient integration, deployment and inference of AI Models in diverse industrial settings This project focuses on advancing MLOps architectures to…
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Doctoral project: Document Classification and Entity Extraction Many aspects of accounting present difficulties in achieving full automation due to the abundance of unstructured information, such as…
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Seed project: Mitigating Health Inequalities in the Kronoberg Region - A Transdisciplinary System Thinking Approach The main objective for this seed project within the Knowledge environment Digital…
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Seed project: Using Natural Language Models for Extracting Drug-Related Problems (NLMED) The overall goal of the research in this seed project within the Linnaeus University Center for Data Intensive…
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Seed project: Development of an intelligent wearable – the DIWAH study The overall goal of the research in this seeding project within the Linnaeus University Center for Data Intensive Sciences and…
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Seed project: Investigate Machine Learning Techniques for Decision-Making Support in K-12 Educational Context The main aim of this seed application is to investigate the use and application of Machine…
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Doctoral project: Reuse of health data, combing the best of two worlds A method for automatic generation of features with high predictive power based on domain knowledge.
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Project: Climate-driven power management in Crossways The purpose of the feasibility study is to investigate how we can best meet the energy and climate challenges that lie ahead. We need to balance a…
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Doctoral project: Realising smarter organization by developing Digital Twin of the Organization A Digital Twin of an Organization (DTO) as a software component proposes a live model of an…
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Doctoral project: Digital Twin as a Service (DTaaS) This doctoral project targets to work on Digital Twin, with integration to data intensive sources.
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Smarter Systems We want to build systems that are a little smarter, that is, systems that make decisions independently and adjust to become a little better at solving their tasks. Our research and…
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Smart Industry Group Smart Industry Group (SIG) is an interdisciplinary research group featuring expertise from computer science and mechanical engineering. SIG's focus is making production and…