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Dortmund, we invite applications for a PhD Candidate (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM) You will be responsible for Developing new machine learning algorithms for microscopy image
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formulation, which displays striking similarities to that used by the Computational Fluid Dynamics (CFD) community, has inspired the investigators to adopt conventional CFD algorithms in the novel context
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and innovation catalyst, in this exciting project, you will develop novel algorithms to monitor and analyse workers' movements, detect harmful movement patterns, and implement simple intervention
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Award summary This studentship provides an annual living allowance (stipend) of £21,470, and full tuition fees (Home fee level only). Overview This project will develop uncertainty quantification
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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quantitative analysis skills and experience developing algorithms and/or conducting statistical analyses with biological datasets. Background and work knowledge in statistics, algorithms, optimization of novel
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This doctoral research will focus on the development, optimisation, and coordinated deployment of advanced aerial platforms, specifically electric vertical take-off and landing vehicles (eVTOLs) and
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experimentation with Asst. Prof. Eli N. Weinstein. Your goal will be to develop fundamental algorithmic techniques to overcome critical bottlenecks on data scale and quality, enabling scientists to gather vastly
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for Robotic and Autonomous Perception This project aims to make robotic perception systems safer and more reliable by developing new techniques that continuously monitor the performance of their machine
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such as textiles. 2. Proven ability to develop and implement advanced motion-planning algorithms and real-time control schemes, ideally demonstrated through digital-twin simulations and hardware-in-the-loop