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-year master's degree and with an interest in simulation and machine learning. This position is funded under the DTU-JRC Collaborative Doctoral Partnership. Responsibilities and qualifications Your
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predictive maintenance models combining physical and ML approaches. Test, validate, and integrate developed solutions in real industrial environments. You must have a two-year master's degree (120 ECTS points
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their universities. To be considered the applicant must have a basic education at master's level (corresponding to the 3 + 2 Bologna process) have received the grade of 10 (or equivalent) for the master's thesis
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: Motivated cover letter Special PhD application form (available here ) Curriculum vitae Bachelor's and Master’s degrees or equivalent (copy of original + verified English translation) A complete list of
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thermochemical TES. Your main supervisor will be Prof Adriano Sciacovelli and you will join the Thermal Energy Section at DTU Construct. Your work will contribute to a paradigm shift in how complex TES systems
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skills as well as good communication skills in English. You should have completed a two-year master's degree (120 ECTS points) in Mechanical, Production, Materials, Industrial or Robotics Engineering
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is highly desirable. The candidate should have good analytical skills as well as good communication skills in English. You should have completed a two-year master's degree (120 ECTS points) in
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skills as well as good communication skills in English. You should have completed a two-year master's degree (120 ECTS points) in Mechanical, Production, Materials, Industrial or Robotics Engineering
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Software Defined Vehicles (SDV). The primary objective is to expand, mature, and industrialize a novel European RISC-V automotive ecosystem that enables next-generation high-performance European automotive
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involved in the daily supervision of master and bachelor students. You will publish and present your work both at international conferences and in scientific journals with high impact. You will assist in