PERSEUS - PhD Candidate within BigData and AI for Future Mobility Solutions

Updated: 7 days ago
Deadline: 01 Sep 2022

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About the position

The Department of Engineering Cybernetics (ITK) is looking for a PhD candidate in the area of Big Data and Artificial Intelligence for a sustainable and carbon-neutral mobility future. The aim of the PhD will be to develop and exploit big data and artificial intelligence-driven digital twin of urban mobility infrastructures to solve challenges in achieving a carbon-neutral mobility future. A digital twin is defined as a virtual representation of a physical asset or process enabled through data and simulators for real-time prediction, optimization, monitoring, control, and improved decision making. The PhD will work towards developing enabling technologies to instill physical realism in such a digital twin. The enabling technologies will consist of data acquisition, pre-processing, fusion, and postprocessing techniques using an array of physics-based, data-driven, and hybrid models. In addition, the work will also involve the development of tools for communicating insights in a way that facilitates informed public opinion building and decision-making.

The PhD position is part of a new large interdisciplinary initiative called Mobility Lab Elgeseter. The center is divided into the three focus areas 1) stakeholder needs for good mobility, 2) mobility as a system / transportation models, and 3) digital technologies for green mobility, that will work closely together to realize innovative and sustainable future mobility solutions in the urban environment. Within area 3) various enabling technologies will be used to automate the process of building and using digital mobility infrastructure twins (i.e. holistic/unified, life cycle, hierarchical, integrated, dynamic/updated representations of the physical road network) for collaboration, simulation, carbon/energy footprint calculations, road condition monitoring, predictive maintenance, automated traffic management and other forms for value creation (general knowledge will be developed that can be scaled up and used elsewhere).


To realize the objectives of focus area 3) several PhD candidates with partly overlapping competences will work closely together, each focusing on one of the following technology areas: 1) baseline Digital Mobility Twin (DMT) using site surveys and available geo-located data, 2) dynamically updated DMT using IoT, sensors, 5G and edge computing, 3) BigData and AI (this PhD position)  to create value from all the sensor data sent from the physical twin, e.g. in the form of decision support and automation, 4) autonomy and simulation to train AI agents and simulate “what-if” scenarios, and 5) XR and Visualization to interact with the DMT throughout its life-cycle (construction and use) and increase citizens engagement and feedback before things have been built physically.

Throughout the overall Mobility Lab Elgeseter project there will be tight interaction with the other two focus areas, e.g. providing sensor data and visualizations to the two other areas, get feedback from area 1) regarding user needs and integrate transportation models from 2) in the DMT.

This PhD project is also part of the PERSEUS doctoral program that will contribute to a smarter, safer, and more sustainable future by approaching important challenges within key enabling technologies (Big data and AI, Digital Twins, Internet of Things, Extended Reality, and Information and Cyber Security). PERSEUS is a collaboration between NTNU, 11 top-level academic partners in 8 European countries, and 8 industrial partners within sectors of high societal relevance. The PERSEUS PhD candidates will have the opportunity to collaborate with researchers in the partner institutions and in other project consortia, and benefit from these collaborative research and education activities. This includes a 2–3 month international stay and a 1-2 month national stay with one of the PERSEUS partners.

The position's working place will be the NTNU campus in Trondheim and you will report to Prof. Adil Rasheed.


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