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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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-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