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optics will be an advantage. You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree. The details, responsibilities
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must not have resided or carried out your main activity (work, studies, etc.) in Denmark for more than 12 months in the 3 years immediately prior to the recruitment date. Project Responsibilities As a
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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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analyses Demonstrated research background, inclusive of master thesis or articles published on pertinent subjects (e.g., time series analyses, ocean sensors, acoustic and optical data processing, automation
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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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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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, laboratory testing and data augmentation. Your main goal will be to develop predictive models for assessing the degradability of bioplastics, facilitating a transition to more sustainable materials. More
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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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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