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Field
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machine learning; acoustic signal processing enhanced by ML; human-in-the-loop/active-learning methods; representation learning; analysing sound sequences and vocal interactions; category discovery; Perma
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also take an active role in group activities, such as master and PhD student education, presentation of your work, maintenance of lab organization, and societal and stakeholder outreach. What we ask
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the Electrical Energy Systems group, collaborating closely with PhD students, postdocs, and process and materials partners in a supportive, multidisciplinary team. What you will deliver A quantitative
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combine research in Remote Sensing and AI with teaching and student supervision? Have you recently earned a PhD in Remote Sensing, or are you about to finish your PhD, and feel inspired to share your
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energised — not deterred — by problems that sit between physics, learning and the messy real world. Your experience and profile: a PhD (completed or near completion) in Machine Learning, Computer Vision
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-disciplinary domain. Specific research topics to apply to bioacoustics might include: low-footprint machine learning; acoustic signal processing enhanced by ML; human-in-the-loop/active-learning methods
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or cryo-ET sample preparation, data collection and image processing is particularly valuable. You are interested in understanding molecular mechanisms of host–pathogen interactions and are willing
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in close collaboration with Sjoerd Dirksen , Johannes Maly , and a PhD student that will start at the Ludwig-Maximilians-Universität (LMU) in Munich, Germany. During the project, you will spend two
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ranging from (bio)chemistry and physics to bioinformatics and cell biology. Our drive is to push boundaries in our aim to visualise molecular processes in their native context and at the highest possible
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tasking in real time. The fellowship will investigate how mission planning can evolve from static scheduling to an adaptive, intelligence-driven process executed directly on board satellites. This includes