Sort by
Refine Your Search
-
Category
-
Program
-
Field
-
Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD Position: Computational Design and Digital Fabrication of high-performance timber plate structures
-
electronic structure calculations to explore the phase diagram and relevant properties of layered Ruddlesden-Popper-type nickelates. Project background Layered nickelates of the Ruddlesden-Popper series have
-
. These materials-ranging from structural to water-soluble polymers-are designed for complete microbial metabolic utilization in their intended receiving environments (e.g., aquatic systems, soils, wastewater). By
-
identify structures with improved stability, performance, and scalability. At ETH Zurich, this work is embedded in an interdisciplinary research environment spanning organic and inorganic synthesis
-
at both ETH Zurich and Eawag. Job description The successful candidate will conduct fundamental research on WS/DP adsorption and establish (semi-)quantitative polymer structure–adsorption relationships by
-
remote sensing missions. The team’s work bridges earth observation with applied forest monitoring, including tree species identification, forest structural changes, and forest resilience assessments, with
-
in protein engineering and drug delivery on an innovative research challenge. Apply their expertise in designing structure-based peptide ligands and peptide conjugates. Develop affinity-based screens
-
Zurich is the leading institute for applied research in economics in Switzerland. KOF conducts well-founded and independent research on the Swiss and international economy. It addresses structural and
-
CCS. Your main tasks will include: Processing and imaging the newly acquired high-density 3D seismic dataset and integrating vintage 3D seismic data to image and characterise the geological structures
-
, indicators and survey information. The division combines structural macroeconometric modelling with data-science methods for nowcasting, high-frequency indicators construction, machine learning, time-series