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Are you passionate about mathematical control theory and its applications? Are you eager to develop estimation and control algorithms for large-scale dynamical systems with the aim of making next
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of AI for the integration of multimodal healthcare data specifically incorporating patient preferences. This includes investigating new methods but also designing and benchmarking integration algorithms
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designing and benchmarking integration algorithms. The position is situated in the Intelligent Data Engineering Lab and will be supervised by Dr. Jan-Christoph Kalo and Prof. Paul Groth. What you will do
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advantage may arise. The focus 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
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/transformative innovation to help develop innovative EO solutions. We offer: a stimulating multinational, interdisciplinary and open work environment; access to high-performance computing infrastructure and
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Join a cutting-edge project developing automated IR spectroscopy tools for solid sampling - ideal for those passionate about spectroscopy, hardware and data science. Job requirements This project
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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
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Description Join a cutting-edge project developing automated IR spectroscopy tools for solid sampling - ideal for those passionate about spectroscopy, hardware and data science. Job requirements This project
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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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image processing and analysis method development. The position builds on the lab's track-record in the field of computational imaging techniques for super-resolution microscopy and image analysis