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Field
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-guided medical applications, with a focus on advanced robotics. You will work directly with clinical data to design robust, efficient deep learning algorithms that maximize the information extracted from
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algorithms. We welcome applications from individuals with experience in: Experience developing deep learning models for real-time image/video segmentation, object tracking, reinforcement learning. Deep
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computational methods for the analysis and integration of –omics data. The group has a strong track record in (integrative) computational omics analysis, algorithm development, machine learning and scientific
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); units such as onboard computers, mass memories, remote terminals and instrument control units*; digital and analogue signal processing electronics for payload/platform functions; front-end acquisition and
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AI-applications to help solve problems such as disinformation, algorithmic bias and filter bubbles. Together with our partners we will also (co)-create new ethical and legal frameworks for responsible
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Challenge: Control robotic dexterous hand during dynamic movements
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-time control algorithms, and validate performance across diverse scenarios. You'll be part of the Tactile Machines Lab, which is a dynamic, interdisciplinary group of researcher bringing together
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Today, companies across a wide
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”, connecting EO with a growing ecosystem of disruptive and transformative innovation, encompassing AI, ML, quantum computing, edge computing, metamaterials, photonics, etc. Many of the challenges posed by new
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The positions are offered as a postdoc researcher position (0.75/0.8 FTE