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their reliability and resource efficiency during production and operation. The »KI-unterstütze Simulation« team combines physically based simulation approaches with efficient and advanced mathematical algorithms and
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enable the digitisation of strategies for the expert. The concept is also used to describe an algorithm for the development of process parameters to eliminate laser-induced roughness during laser polishing
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an algorithm to be implemented in Python.
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and their processing on the FPGA of a frame grabber card You will program the PC software for configuring and controlling the algorithms on the FPGA Your tasks will include designing the transfer
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, and characterization Develop gate implementations, benchmarking and algorithms Work on the interdisciplinary challenges in systems engineering Install and improve experimental setups and fabrication
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with OSL: Use OSL to implement the PPTBF algorithm in 3D environments: like a couple of point process, feature function and window function. Optimize Procedural Algorithms: Develop more efficient methods
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, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable
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Your Job: Explore bio-inspired algorithms through simulation—both numerical and circuit-based—and experiment with existing hardware, including CMOS and memristor circuits. Additionally, will need
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, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable
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system requires effective orchestration that can schedule the application on these systems. While traditional scheduling algorithms exist, these do not focus on the energy footprint of applications