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platform. Initially, a black box deep learning approach will be implemented. However, due to the need for robustness, transparency, and explainability (e.g. for quality control across sectors), the research
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Position Description The Unsteady Flow Diagnostics Laboratory (UNFoLD) led by Prof. Karen Mulleners at EPFL in Lausanne is looking for multiple PhD students to join the group in the fall of 2025 or early
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project will develop novel methods for modelling and controlling large gossamer satellites (LGSs), so that they can be reliably utilised in space-based solar power (SBSP) applications. The candidate will
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extended from cloud solutions (such as OpenLLMetry), the research question is how to identify anomalies in collected information that can come from multiple AI services either invoked manually by users or by
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-B4 Investigators: Prof. Dr. Meng Wang, Chair of Traffic Process Automation , and co-supervised by another expert in traffic control Requirements: excellent or very good university degree
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in scientific methodologies that have transformed the study of, and interest for bioarchaeological remains, makes the PhD project highly relevant across multiple academic domains. Although the botany
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robots will make current labour-intensive cultivation systems (e.g., stripcropping, targeted mechanical weed control, etc.) profitable, contributing to increased biodiversity locally and reducing the need
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will work on the design, development, and testing of integrated systems that may include laser generation and stabilisation, RF control, PID systems, and embedded electronics. The work aims to improve
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, with three other modeling-focused PhDs who will work at different scales of assessment. This work is embedded into a larger team of PhDs, who are collecting data, working on multiple topics, from ecology
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measurements of key organics, plus culture experiments, to uncover the biochemical pathways and environmental controls on methane formation and oxidation. Your job This work will enhance our understanding