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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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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 robotics). Proficiency in Python, MATLAB, and/or C++ programming dialects (knowledge in other languages will be valued). Marine fieldwork experience with deployed platforms is an advantage. You must
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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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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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of nature. Requirements and programme structure PhD candidates follow an individual PhD plan including course work, conference participation, and teaching. One semester is typically spent at another research
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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