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research project in collaboration with multiple tech companies to develop and demonstrate the next generation of free-space optical (FSO) communication systems for satellite communications. Information
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Location ESAC, Villanueva de la Cañada, Spain Our team and mission Under the direct authority of D/SCI, the Head of the Science Operations Department is responsible for the development
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this PhD project, you will investigate the co-design between event-based learning algorithms and neuronal hardware units with multi-scale time constants. The algorithmic methodology will exploit recent
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well as develop new algorithms for inverse scattering. These extensions will be employed in a reconstruction process on actual measured data from real-world metrology, in line with the long-term vision presented in
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work hands-on with clinical data and build robust deep learning algorithms. We welcome applications from individuals with experience in: Experience developing deep learning models for real-time image
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In this role, you will help develop and implement cutting-edge AI solutions for real-time, image-guided medical applications, with a focus on advanced robotics. You will work directly with clinical
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Are you eager to advance lung cancer diagnostics by developing standardized biomarker assays using state-of-the-art mass spectrometry? Join us as a PhD candidate and contribute to clinically
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. Your work may involve formulating new models, analysing structural properties, and developing innovative algorithms with both theoretical rigor and practical relevance.
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Research Infrastructure? No Offer Description Job description You will explore hardware/algorithm co-design for NeuroAI, simultaneously taking into account scalability inspired by modern AI workloads, as
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of this project is to develop techniques that will enable gate-based quantum optimization algorithms to tackle realistic (large-scale, mixed-integer, and constrained) instances of stochastic programming problems