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applications in information technology and are based on electrical, magnetic or optical functionalities. The Department of Quantum Technologies is looking for a PhD Student (f/m/d) - Imaging magnetic structures
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scope of different subjects such as electrical engineering/electronics, microelectronics, microsystems technology, information technology, computer science, physics, chemistry, optics and manufacturing
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theoretical and/or computational research in Nonequilibrium Statistical Physics and Active Matter, under the supervision of Ramin Golestanian. For more information concerning our current areas of research
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will engage in theoretical and/or computational research in Nonequilibrium Statistical Physics and Active Matter, under the supervision of Ramin Golestanian. For more information concerning our current
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journals What you bring to the table Completed scientific university studies in the field of electrical engineering, electronics, communication engineering, information technology or comparable with a
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machine learning approaches. These are similar to earlier work on charge and excitation energy transfer (see https://constructor.university/comp_phys). The project for the PhD fellowship is slightly more
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student projects and BSc/MSc theses Your Profile: Master’s degree in physics, electrical/electronic engineering, computer science, mathematics, or a related field Strong background in machine learning
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aspects of modern ML systems. Current research directions include the ERC Consolidator Grant CollectiveMinds, which aims to make machine learning more sustainable and efficient by enabling multiple smaller
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current and future disease risk and burden across multiple pathogens with environment- and climate-sensitivity. Your Tasks: Building a diverse set of models for short-term predictions and the long-term
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well as electrical flow. Prototyping of the identified structures via stereolithographic, 3D printing and textile techniques like tufting, machine-based embroidery techniques or non-interlaced 3D pre-forming