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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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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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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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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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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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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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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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project from the grade giving institution. The statement must clearly state that the candidate has been among the top 30 pct. in the graduation class for the study programme. List of publications and
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or dissertation project from the grade giving institution. The statement must clearly state that the candidate has been among the top 30 pct. in the graduation class for the study programme. List of publications