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for the 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
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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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; Synopsys or Mentor Graphics. Strong programming skills: Python and C/C++. Experience in hardware accelerators, in-memory processing, or SoC integration. Strong analytical and problem-solving skills, with
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programme, please see DTU's rules for the PhD education . Assessment The assessment of candidates will be performed by Professor Bengt Johansson, Project leader of the AI controlled engine project and future
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning
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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
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to the PhD Secretariat, Faculty of Health Sciences, to be enrolled as PhD students. The PhD programme will be carried out in accordance with Faculty regulations and the Danish Ministerial Order on the PhD
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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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research projects and programs Strong interest in a long-term commitment to a growing research group Application procedure Before applying the candidates are advised to read the Faculty information