The research in the newly established Multiphase Fluid Dynamics group examines both fundamental and applied questions in various small-scale multiphase fluid phenomena, such as bubble and droplet dynamics and the resulting fast flows. One of our key objectives is to control bubble oscillations to exploit their energy-focusing characteristics. We also develop experimental techniques to observe and characterise high-speed multiphase fluid phenomena optically and acoustically. The group is part of the Institute of Fluid Dynamics, which pursues a broad range of experimental, numerical and theoretical research efforts in a friendly and inclusive environment with state-of-the-art infrastructure.
Starting date: 1 October 2022, or later. Negotiable.
Duration of appointment: Maximum 4 years.
Currently, little is known about cavitation bubble dynamics in complex fluids. We are particularly interested in yield-stress fluids, which form a specific class of non-Newtonian fluids that possess characteristic yield stress below which they may support the imposed external stress elastically but beyond which they no longer act as a solid but rather flow like a viscous fluid. Such viscoplastic behaviour is present in a wide range of soft materials, such as emulsions, foams, detergents, and gels. Cavitation bubble dynamics in such media are relevant in numerous industrial sectors such as additive manufacturing, food industry, cosmetics, and ultrasound-induced degassing and defoaming processes.
We seek to appoint a PhD student to conduct experimental research to discover the effects of material mechanical properties on cavitation bubble dynamics in yield stress fluids and soft elastic solids. You will design your experimental setup by exploiting the state-of-the-art ultra-high-speed imaging, optical and acoustic facilities available in our lab. You will also couple your experimental findings with numerical simulations performed by our collaborators at the Fluid Lab at the Soft Matter Group of University of Amsterdam, the Netherlands (numerical PhD opening of this project can be found here), with whom tight scientific exchange will happen throughout the project. In addition to research, you will contribute to teaching and lab activities in the institute.
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.
The requirements include a Master's degree in mechanical, aeronautical or chemical engineering, physics, material science or a related field. You should be curiosity-driven, creative, open-minded and independent, and have good communication skills, fluency in English and the willingness to fully commit yourself as a part of an international team. You should also have strong interests in experimental fluid mechanics, multi-phase flows, acoustics, and similar. Experience in experimental research is an advantage, but not necessary. However, you should be excited about the prospect of working in a lab.
To apply for this position, please submit:
Applications must be submitted using the online tool, not by e-mail. Applications are accepted until the position is filled.
For more information on our group and on the Institute of Fluid Dynamics, visit the website (www.ifd.ethz.ch) or contact the group leader, Prof Outi Supponen via email at email@example.com (no applications).
Postdoc or Established Researcher position in Structural Geology and TectonicsThe Structural Geology and Tectonics (SGT) group in the Geological Institute, ETH Zurich, Switzerland, is seeking resea...
Student Research Assistant at the Chair of Systems DesignWe are looking for a student research assistant to work on our data project “ DemocraSci – a research platform for data-driven democracy stu...
PhD position at the intersection of neurology, data science, and neuroimagingThe topic of this PhD project concerns an important question in neurology, i.e. whether individual responses to treatmen...
Interdisciplinary PhD position combining iPSC disease modelling, large-scale extracellular electrophysiology and machine learningThe BioEngineering Laboratory at the Department of Biosystems Scienc...