EPFL Professors win four SNSF Eccellenza Grants and one Fellowship

The Swiss National Foundation’s Eccellenza Professorial Fellowships and SNSF Eccellenza Grants are given each year to “highly qualified young researchers who aspire to a permanent professorship.” The goal is to support these scientists in leading generously funded research projects with their own team at a Swiss higher education institution.

The Eccellenza Grants aim at “researchers in all disciplines who have recently been appointed as tenure-track assistant professors at a Swiss higher education institution.” The Grants offer project funds up to 1,500,000 Swiss francs over five years.

The Eccellenza Professorial Fellowships are aimed “at outstanding researchers in all disciplines who have a doctorate or equivalent qualification and are pursuing an academic career, but who have not yet obtained an assistant professorship.” Along with salaries, the Fellowships fund projects up to 1,000,000 Swiss francs over five years.

This year, EPFL Professors have been awarded four Grants and one Fellowship:

Maartje Bastings (School of Engineering). Project: Quantifying complex multivalency through precision engineering (Eccellenza Grant).

“We aim to develop super-specific materials using DNA as precision polymer. By controlling the patterns of different binding molecules, we can systematically and quantitatively analyze the importance of spatial-organization on binding performance. Our precision materials will provide novel insights in multivalent binding which is crucial to improve the design of diagnostics and allows for the development of smart therapeutic nanoparticles.”

Romain Fleury (School of Engineering). Project: Ultra-compact wave devices based on deep subwavelength spatially dispersive effects (Eccellenza Grant).

“We will work on a new class of extraordinarily small devices that can manipulate waves with extremely long wavelengths. This will lead to disruptive advances in processing the information and energy carried by waves such as light and sound, and reach out to several important technological applications, including new, ultra-small and ultra-light telecommunication devices, ultra-compact noise control solutions, or even safe and non-invasive medical imaging systems with unprecedented resolution.”

Johan Gaume (School of Architecture, Civil and Environmental Engineering). Project: Unified modeling of snow and avalanche mechanics using the material point method (Eccellenza Professorial Fellowship).

“Snow is a complex and fascinating material which can switch from solid to fluid states leading to dangerous avalanches. While progress has been made recently, we still lack a unified framework to simulate both the release and the flow of avalanches at the slope scale. Our main objective is to develop a multi-scale and unified approach using the Material Point Method to model snow and avalanche mechanics in order to better understand snow failure and the complex processes involved in snow avalanches.”

Pavan Ramdya (School of Life Sciences/Brain Mind Institute/Interfaculty Institute of Bioengineering). Project: Reverse-engineering and digital reconstruction of a limb control circuit (Eccellenza Grant).

“Robots cannot match the abilities of animals to sense, decide, and act. Focusing on fly (Drosophila melanogaster) behaviors like grooming and locomotion, we aim to reveal how biological limb control circuits use mechanosensory feedback to make precise movements, and how they integrate motor signals and sensory feedback. We will investigate theoretical predictions for biological movement control efficiency, and identify how animals adapt movements across species.”

Christian Theiler (School of Basic Sciences). Project: Alternative divertors for improved tokamak operation (Eccellenza Grant).

“In fusion devices, such as tokamaks, the edge region of the magnetically confined plasma has to simultaneously assure good confinement of the core plasma and guarantee acceptable heat fluxes to the surrounding wall structures. We propose to use EPFL’s Tokamak à Configuration Variable (TCV) to explore alternative magnetic geometries of the tokamak edge region, a promising path to develop a robust tokamak edge solution.”