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of Convolutional Neural Networks (CNNs) and Spiking Neural Networks (SNNs), with a strong emphasis on deploying these models on hardware-constrained edge platforms. The position focuses on developing robust
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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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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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the development of an autonomous outdoor navigation solution as well as the hardware of the robots. Natural outdoor environments like farms and forests are filled with highly complex geometrical forms and
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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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strategies individually and in cooperative work Self-assured and determined manner with good communication skills for a convincing presentation, even in complex technical contexts Strong and open communication
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testing as well as micropumps. The close collaboration between our experts not only creates groundbreaking innovations, but also synergies that enable Fraunhofer EMFT to effectively master the complex
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control of decentralized, local energy systems for network integration. One of our main research interests is cross-sector applications with hydrogen systems. On the control side, our current research
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developing applications to enhance grid planning and operation, and exploring the integration of inverter-based units into existing grid infrastructures. Additionally, we create dynamic models of networks and
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the integration of both Convolutional Neural Networks (CNNs) and Spiking Neural Networks (SNNs). This position will involve training and optimizing these neural networks using Python frameworks, including CUDA