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to dimension the reserves for balancing these power systems with manual and automatic reserves such as mFRR, aFRR and FCR. This PhD project will model different balancing principles including MARI and PICASSO
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twins, energy islands, electrolyzers, and machine learning. Our team of 25 members (link ) from 13 different nationalities values diversity and includes experts in a broad range of scientific disciplines
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components are in use. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process
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; Synopsys or Mentor Graphics. Strong programming skills: Python and C/C++. Experience in hardware accelerators, in-memory processing, or SoC integration. Strong analytical and problem-solving skills, with
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Experience with VLSI design (Cadence tools, Verilog/VHDL, SPICE) Knowledge of neural networks and neuromorphic systems is a strong advantage Good programming skills (e.g., Python, MATLAB) and interest in
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at least one programming language (preferably Python) and experience with AI applications in manufacturing are expected. A motivated, collaborative person who is able to work in an international and