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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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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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completed 1 year of relevant MSc studies. The hired candidates will be part of the section of Artificial Intelligence, Cybersecurity, and Programming Languages (ACP), an ambitious group that fosters
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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