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programming and know how to use version control. ▪ You are experienced in the usage of machine learning (e.g., Actor-critic algorithms, deep neural networks, support vector machines, unsupervised learning
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Appropriate computational skills and knowledge of programming languages (Python, C++, etc.) Experience with Machine and Deep Learning models and software (Keras, Scikit-Learn, Convolutional Neural Networks, etc
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” highly flexible components and ensure their energy harvesting capabilities. This project will contribute to ambitious plans for SBSP as a vital part of the future Net Zero landscape. Recent advances in
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mentoring by a team of two interdisciplinary professors, RTG-specific scientific and personal development workshops, networking with academic and industrial leaders, the participation in national and
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? We invite applications for a PhD position, focusing on the design and implementation of Spiking Neural Networks (SNNs) using CMOS technology. Project Overview This PhD position is part of a
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environment for all PGRs creating a strong sense of community across research disciplines. Community and research culture is important to our PGRs and the FoE support this by working closely with our
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, research visits, and other activities to promote a strong multidisciplinary and international network between PhD students, postdocs, researchers, and industry. Who we are looking for The following
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Degree PhD "Medical Research", Dr rer nat, Dr rer biol hum, Dr med Course location München Teaching language English Languages Courses and lectures are held in English. Programme duration 6
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investigate and develop innovative memory solutions in advanced CMOS technologies such as FDSOI. The development of integrated circuits also plays an important role in making these networked devices and their
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this, the impact of the heterogeneity in the structure of the individuals contact network on disease transmission will be investigated. The candidate will gain experience in a range of mathematical and computational