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Analytics. The core focus of the PhD project will be to develop and test planning and optimization models to analyze new and innovative Hospital-at-Home systems to improve access to healthcare for elderly and
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analytical techniques to assess materials in both pre- and post-consumer shoes. The project aims to: Map footwear waste flows in Europe by building a database of common materials in selected footwear
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sampling and characterization methods to analyze the composition of current footwear. This includes applying advanced analytical techniques to assess materials in both pre- and post-consumer shoes
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fields. Experience with 3D printing and/or soft robotics is an advantage Familiarity with sensor integration and control systems Analytical thinking, problem-solving skills, and effective communication
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, innovative, and collaborative PhD fellow with: A recent academic education with a master’s degree in biochemistry, biomedicine, molecular biology, protein science, analytical biochemistry, or similar field
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systems Strong analytical skills and interest in interdisciplinary, real-world problem solving Good communication skills in English and the ability to collaborate with diverse stakeholders You must have a
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at DTU Compute, including teaching and supervision activities We are looking for you who have: Solid knowledge of process mining, continual learning, or cybersecurity Strong analytical and programming
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such as CAPeX. You are an experimentalist - second to none. You have experience in one or more of the following areas: Analytical electrochemistry Vacuum science/surface science MEMS chip design and
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-throughput experimental techniques. Strong analytical skills and the ability to work effectively in a collaborative, interdisciplinary research environment. Approval and Enrolment The scholarship for the PhD
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into the enzyme-substrate interaction in the same set of enzymes. Further, there will be collaboration with a PhD student from NTNU working with similar analytical methods on another class of carbohydrate-active