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Completed Research pairs projects

The funding instrument Research pairs is intended to foster collaboration between two young researchers that have obtained their doctoral degrees not more than ten years ago at the time of application. The researchers in the pair should belong to either i) two different KTH schools, ii) KTH school and RISE/Stockholm University, or iii) RISE and Stockholm University.

The instrument is aimed to identify new research collaborations that have potential to develop into a leading scientific activity over the next three to five years and therefore be a vehicle for supporting and promoting young scholars with the potential to become future digital leaders. The 2-year projects should address cutting-edge research within subject areas at the intersection of the Research matrix and should involve researchers that complement each other and conduct interdisciplinary research.

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Autonomous coordination and control of smart converters for sustainable power systems

Autonomous coordination and control of smart converters for sustainable power systems

Developing smart autonomous power converters for optimal support of electric power systems...

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Characterization of the mechanical tissue properties of the brain in the developing brain with magnetic resonance elastography

Characterization of the mechanical tissue properties of the brain in the developing brain with magnetic resonance elastography

Improving the diagnosis and treatment of anxiety disorders in the young population...

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Digital twins of human neuromusculoskeletal system: A new paradigm of personalized medicine in neuro-rehabilitation

Digital twins of human neuromusculoskeletal system: A new paradigm of personalized medicine in neuro-rehabilitation

Integrating the latest developments in personalized neuromusculoskeletal modelling, innovative...

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Enabling Machine-Learning Intelligence for Network Cybersecurity

Enabling Machine-Learning Intelligence for Network Cybersecurity

Design and implementation of a framework that reconciles the different speeds at which today’s networks and machine learning systems operate...

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Engineering biodegradable components for packaging digitalization

Engineering biodegradable components for packaging digitalization

Develop biodegradable recording platforms for digital technologies that capture biological signals and safely integrate them into life and the environment...

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Layering Trust in Intimate Digital Health Technologies

Layering Trust in Intimate Digital Health Technologies

Natural Cycles offers an algorithmic contraceptive option to more than 700,000 users worldwide and provides an excellent testbed for studying how trust is developed...

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Resilient Decentralized Computing: Enabling Trust and Simplicity in Smart Edge Services

Resilient Decentralized Computing: Enabling Trust and Simplicity in Smart Edge Services

A new approach to rapidly build continuous, trusted and scalable applications with built-in resilience and privacy...

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SOS: Empowering User Control over Sensitive IoT Data

SOS: Empowering User Control over Sensitive IoT Data

Enabling users to securely store data in confidential cloud enclaves and automate the interaction between IoT) devices via provably secure...

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Threat models for cyber insurance

Threat models for cyber insurance

Designing a threat modelling and attack simulation language, insuranceLang, for cyber insurance...

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Using Neuroimaging Data for Exploring Conversational Engagement in Human-Robot Interaction

Using Neuroimaging Data for Exploring Conversational Engagement in Human-Robot Interaction

Address interactions with novel conversational systems, such as social robots, and digital assistants...

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