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To bridge the gap between existing cloud-based ICT architectures and large scale IoT deployment, edge computing is becoming a promising paradigm to facilitate computing and communication for the next generation cyber-physical infrastructures. The key features of edge computing include low latency, locality, scalability, security and privacy. Those features form a solid foundation to meet the service requirements of smart cyber-physical systems. However, although there are stand-alone solutions exist already in this domain, the self-adaptiveness and resilience aspects are still unexplored yet in practical context. In addition, we lack a coherent edge computing architecture that embeds these two principles and can effectively enhance our cyber-physical infrastructures.The offered PhD position is for a research project to investigate how to enhance self-adaptiveness and resilience in cyber-physical systems. The focus is on edge computing, which encompasses computing, communication, data analytics, security and privacy. In line with 5G and IoT development, the major pursuit is on large scale IoT deployment in smart urban infrastructures such as energy and transport systems. In this context, the crucial threats, vulnerabilities, cascading consequences and also mitigation mechanisms across cyber and physical spaces will be studied through the project. In specific, the research is expected to tackle the following questions: 1) What are the key self-adaptiveness and resilience requirements in IoT-enabled transport and energy systems, from both technical and social perspectives? 2) How to integrate edge architecture and embed these two principles into future smart mobility and energy systems? 3) What are the economical and societal impacts from the proposed edge architectures in those environments? and 4) How to effectively combine standardization and policy strategies to facilitate the adoption of the proposed edge architectures?
During the PhD, the candidate will conduct this research and prepare scientific articles presenting the research at conferences and in journals. To enable the candidate to do this successfully, TU Delft offers personal and professional training courses in the form of a graduate school, in which the candidate will participate (the fee is paid by the project and there are no additional costs for this). Furthermore, in addition to her/his scientific supervisors, the applicant will receive an independent senior research as mentor, to aid her personal career development.
The candidate must have a master's degree at the start of the appointment in computer science, information science, engineering, or a similar degree with an academic level equivalent to the master's degree in engineering. Excellent academic records in analytical, mathematical and programming (Python/Java/C++) are preferred. Good command of spoken and written English is required. Development experience with mobile, transport or energy systems is a plus.
The position entails the following tasks: 1) Investigate existing cloud and edge architecture designs and identify requirement gaps for self-adaptiveness and resilience, especially under crucial situations, e.g., cyber-attacks, power failures, nature disasters. 2) Analyze the requirements for smart mobility and energy systems, from both technical and social angles. 3) Design and develop fundamental building blocks such as models, protocols, framework, and policy strategies for the proposed edge architecture. 4) Carry out experimental measurements and analytical studies to evaluate the design. 5) Contribute to teaching activities at ESS department.
TU Delft offers a customisable compensation package, a discount for health insurance ans sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children's centre offers childcare and an international primary school. Dual Career Services offers to accompanying partners. Salary and benefits are in accordace with the Collective Labour Agreement for Dutch Universities.
As a PhD candidate you will be enrolled in the TU Delft Graduate School. TU Delft Graduate School provides an inspiring research environment; an excellent team of supervisors, academic staff and a mentor; and a Doctoral Education Programme aimed at developing your transferable, discipline-related and research skills. Please visit www.tudelft.nl/phd for more information.
Delft University of Technology (TU Delft) is a multifaceted institution offering education and carrying out research in the technical sciences at an internationally recognised level. Education, research and design are strongly oriented towards applicability. TU Delft develops technologies for future generations, focusing on sustainability, safety and economic vitality. At TU Delft you will work in an environment where technical sciences and society converge. TU Delft comprises eight faculties, unique laboratories, research institutes and schools.
The Faculty of TPM contributes to sustainable solutions for technological challenges in society by combining the insights from engineering with the humanities and the social sciences. The PhD candidate will be positioned in the Engineering Systems and Services (ESS) department of TPM. The core activity of the department is to model, understand, forecast, and shape emerging technological innovations and user patterns in the increasingly interconnected sectors of energy, mobility and ICT, and use these insights for improved design, regulation and operation of such engineering systems.
The ESS department sees edge computing as an important and growing area of research for building interoperable, flexible, resilient, scalable and secure cyber-physical infrastructures. Our research contributes to foster a cooperative and resilient computing ecosystem that can scale to the IoT growth, and help forge a new channel for innovation. The research sheds light on how to achieve long-term sustainability in the next generation cyber-physical systems, i.e., smart transport and energy systems. In this context, we are looking for PhD candidate interested in research on designing, developing, and analyzing edge-driven architectures to achieve self-adaptiveness and resilience.