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Field
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and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty
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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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student projects and BSc/MSc theses Your Profile: Master’s degree in physics, electrical/electronic engineering, computer science, mathematics, or a related field Strong background in machine learning
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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 discipline
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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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of topics is covered, from large-scale data management to data mining and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics
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strengthen the data science and machine learning activities of the IAS-9 with exciting new topics. You will work in a multidisciplinary team of enthusiastic data scientists, software developers and domain
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the opportunity to contribute to collaborative efforts at the interface of data science, imaging, and materials research. You will strengthen the data science and machine learning activities of the IAS-9 with
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domains are e.g., signal-/image processing, artificial intelligence and machine learning. Tasks: research and development in designing and programming field programmable gate arrays (FPGAs) for accelerating
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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