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with, cloud computing and virtualisation technologies Familiarity and hands-on experience with machine learning techniques desirable Desirable to have work experience (through internships or similar) in
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off-the-shelf sensors and the development of resilient algorithms that combine first-principles modeling with modern machine learning techniques. The goal is to push the boundaries of robust perception
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applications for a PhD Student or Postdoc Position (f/m/d) for any of the following topics: Combining non-equilibrium alchemistry with machine learning Free energy calculations for enzyme design Permeation and
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processing and machine learning methods, and big data analytics solutions to extract highly accurate large-scale geo-information from big Earth observation data. Our team aims at tackling societal grand
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, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power
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. Strong coding skills for programming neural networks, machine learning and machine learning software frameworks (e.g. PyTorch or Jax) is a must. The ability for creative and analytical thinking across
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that the programme will combine ideas from a broad range of disciplines, including machine learning, control theory, differential equations, port-Hamiltonian systems theory, modelling of power systems, digital signal
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that exhibit emergent turbulent behaviors, and (2) disordered optical media that process information through complex light scattering patterns. Using advanced imaging, machine learning techniques, and real-time
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focus will be on biomechanics, image processing, machine learning (ML), artificial intelligence (AI), and metrology, the student will also contribute to the co-design of cadaver experiments and data
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. Fe, S) on CNT purity and structure. Evaluate CNTs as conductive additives in standard Li-ion battery electrodes. Apply AI/machine learning to optimise experimental design and growth parameters