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explored using scientific machine leaning. Machine learning, programming experience and a curious mind-set You are fascinated by how computers can learn from data and you have a strong interest in the
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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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promotes sustainable economic growth and higher levels of technological innovation. It will benefit society and create a safer and smarter world by providing decent work for all. Furthermore, autonomous
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: first, establishing a robust data foundation; second, designing a modular and open digital platform; and third, developing a predictive maintenance application as a proof of concept. Responsibilities and
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, or biophysics. Experience with experimental organic chemistry, NMR, kinetic modelling and/or cheminformatics are advantages. The candidate must be able to work independently, but also participate in
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on developing energy-efficient, privacy-preserving IoT systems to enable proactive elderly care at home. More specifically the main responsibilities of the PhD candidate will include: Designing and deploying
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mechanics (nonlinear beam theory, fluid-structure interaction) Desire to develop interdisciplinary expertise across hydrodynamics and structural mechanics. Experience with or willingness to learn: Programming
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during emergencies and is based on high-temperature PEM (HT-PEM) technology. The HT-PEM stacks operate at approximately 160 °C, offering simplified designs and operational advantages, including improved
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. This knowledge will support the designation of marine protected areas in line with the “30 by 30” conservation target. A central component of the project is the integration and analysis of diverse data sources