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more sustainable? If you share our passion for technology and the difference it can make in meeting the UN’s Sustainable Development Goals, perhaps you are one of our two new PhD students. At DTU Electro
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algorithms. Graph Neural Networks. The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another field
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-tasks and language models. This position is part of SDU’s initiative to develop energy-efficient AI accelerators based on alternative model architectures that cannot be leveraged as efficiently
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on preferences the candidates will work along one (or more) of the following different directions: theoretical foundation involving quantitative models (e.g. stochastic, timed weighted, hybrid automata) and logics
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create a closed loop pipeline able to rapidly design binders to any target and optimized for developability. The program is rooted in DALSA (DTU’s Arena for Life Science Automation), a new
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(entities) given the rules and the rules given the molecules. The aim of this project is to develop a theory and accompanying algorithms to decide if an abstract system can be instantiated by a concrete
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electricity price signals, demand-response mechanisms, and time-of-use optimization. AI-Driven Optimization using Reinforcement Learning: Apply RL algorithms to develop and train agents that optimize power
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algorithm. Design methods: Develop novel control methods for power electronic converters feeding electric machine Simulation: Learn advanced simulation tools such as Ansys to simulate and analyze the effect
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and fabrication. The ideal candidates have extensive experience with: Programming of IO boards (STM32, Pixhawk, BeagleBone, etc.) in different programming languages (C++, Python, etc.), MATLAB/Simulink