PhD position in Designing Anti-fragile Large-Scale Traffic Frameworks in Zürich

The Traffic Engineering group (SVT) of the Institute for Transport Planning and Systems (IVT) at ETH Zurich intends to develop scalable optimization systems for operational support in large-scale road networks. We want to cultivate international collaboration with industrial/research partners towards sustainable, robust, resilient and anti-fragile future traffic systems.

Modeling and simulation are moving from being powerful development and analysis tools towards having increased roles in operational monitoring, control and decision support, in which models of specific entities are continually updated. However, current optimization systems are largely the result of tailored technical solutions that are difficult to scale. This project aims to infuse the concept of anti-fragility into the optimization process. Anti-fragility emerges under a volatile, random, and uncertain environment and can bring the system in a state superior to robustness – where it can gain from such an environment. Instead of designing systems to meet known requirements that will always lead to fragile systems at some degree, systems should be designed, wherever possible, to be anti-fragile, i.e. cyber-physical systems (e.g. anti-fragile predictive systems) that can learn from their experience, adapt to unforeseen events they face in their environment, and grow stronger in the face of adversity. The motivation for the proposed project is the development of an anti-fragile traffic engineering framework that is invariant to data scaling, can exploit volatility and uncertainty in the traffic dynamics, and benefit from the uncertainty inherent in such large-scale nonlinear systems. Any such solution should be robust and resilient, while respecting four main principles; adaptability, autonomic re-calibration, self-configuration and reinforced performance improvement.

The doctoral researcher is expected to conduct research in the following areas:

• Road traffic estimation and control for real-world large-scale networks
• ML-based modeling and data-driven control towards future transport networks
• Mathematical modelling and AI-based parameter optimization in an anti-fragile frameworks
• Traffic engineering simulations

We envisage for tackling the challenge of designing real-world systems through a shared approach where academia and practice develop together solutions in an open constructive environment of continuous feedback. We thus expect a doctoral student being able to have regular frequent interaction and presence on relevant research with the "Lamport" Group for Applied AI and High Performance Systems at the Huawei Research Center in Munich, and time and excellent opportunities for development of academic result, under the supervision at ETH Zurich.

You ideally have a Master’s Degree in engineering, applied mathematics, computer science or related fields. You are highly motivated, determined, you have excellent communication and writing skills (proficient spoken and written English is required).

Moreover, the following skills are expected of a promising candidate:

• Computer science and hands-on experience with programming on machine learning, neural networks and/or data analysis.
• Non-linear traffic dynamics and good understanding in traffic route choice, especially its behavioral foundations.
• Interesting in mathematical optimization and control sciences.
• Experience on traffic simulation and modeling is considered an advantage.
• Team working and communication skills. Knowledge of German language is a plus.

The applicant is expected to:

• Publish in top journals and scientific conferences.
• Participate in research proposal preparation.
• Guide/follow semester projects at BSc/MSc level.
• If applicable teach within the SVT course programme.
• Contribute to the operation of the group and the Institute.

You enjoy working in an interactive international environment with other doctoral students, post-docs and senior scientists, referring continuously to practical problems and solutions. You have a keen interest in traffic engineering. This position will be available as of September 2022 or upon agreement.

ETH Zurich is a family-friendly employer with excellent working conditions. You can look forward to an exciting working environment, cultural diversity and attractive offers and benefits.

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