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equivalent to a two-year master's degree in mathematics, physics, computer science, electrical engineering or closely related fields with a focus on computer vision, machine learning or robotics A strong
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for Quantitative Sustainability Assessment of the Department of Environmental and Resource Engineering (DTU Sustain). The section spearheads the development of sustainability assessment methods. You will become part
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latest predictive and generative AI for materials, we can offer you the best possible foundation. We seek two highly motivated and talented PhD students to join our group at DTU Compute, and we offer
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collaboration with DTU Bioengineering and DTU Electro. We emphasize the following required qualifications and skills: Strong foundation in Mechanical Engineering, Materials Engineering, Manufacturing or related
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biology, or analytical workflows. Interest in single-cell analysis, cancer biology, and translational research. Basic level expertise in computational biology (e.g., bioinformatics, machine learning), with
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(DTU), we are offering a fully funded PhD position focused on understanding and mitigating the environmental and health impacts of footwear materials. This research sits at the cutting edge of waste and
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: Expertise in X-ray diffraction and computed tomography Experience in electrochemical characterization of materials Experience with crystal structures analysis and Rietveld refinement Experience in working