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Field
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, digital pathology, whole-slide image analysis, self-supervised learning, foundation models, multiple-instance learning or high-performance computing is an advantage. Prior knowledge of pathology or breast
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and the various components of the tumour microenvironment. The research will primarily be conducted using patient-derived glioblastoma models and will combine approaches from cell and molecular biology
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scale radar datasets with high quality labels remain scarce. In this PhD project, you will investigate foundation models for automotive imaging radar. The goal is to learn general radar representations
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position: Multi-scale Modelling and Experimental Assessment of Volumetrically Prestressed Concrete Your tasks The tasks of the PhD at ETHZ and Empa within the framework of SURPASS are as follows: Volumetric
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Candidates should demonstrate experience and/or knowledge in one or more of the following areas: Numerical modelling of materials and structures using the Finite Element Method (FEM). Simulation of damage and
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Empa within the framework of SURPASS are as follows: Volumetric prestressing of cast and 3D-printable SURPASS overlays using Fe-SMA fibres. Meso-scale finite element modelling of volumetric prestressing
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]. This is not an easy task due to the lack of knowledge in browning reactions for dried dairy products. Some studies have been carried out on liquid model systems and kinetic models have been proposed [3] but
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. To address this challenge, the project aims to develop structural health monitoring technologies based on a digital twin. The digital twin will combine information from the physical structure with models and
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or genetic perturbation-as prior information, complementing or extending curated pathway knowledge. This combination allows us to move beyond purely associative integration toward structure-aware, causally
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developing representations, using neuroimaging with fMRI and OPM-MEG, and to model the developmental process using computational models from AI. The project aims to better understand infant cognition, develop