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enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education
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study programme. List of publications and maximum 2 examples of relevant publications (in case you have any publications). References may be included, you're welcome to use the form for reference letter
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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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three of the following areas: Python programming Develop LLM-based tools to automate data connector generation for data ingestion. Design and implement a multi-layered storage strategy for scalable PBM
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approval, and the candidates will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see
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of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment of the applicants will be made by Associate Professor Roberto Galeazzi and Associate Professor Dimitrios
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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
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hardware description language such as Chisel, VDHL, or Verilog. Knowing Chisel is a bonus. Knowledge of real-time systems System programming in C You must have a two-year master's degree (120 ECTS points
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equivalent to a two-year master's degree. Additional qualifications include: Good programming skills in Python, Julia, R or similar, and familiarity with C, C# or C++. Curiosity and interest in future urban
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of an application for the specific project formulated by the applicant. The PhD study must be completed in accordance with The Ministerial Order on the PhD programme (2013) and the Faculty’s rules on achieving