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renewable energy systems playing a pivotal role in transitioning away from fossil fuels. Wind turbines, solar photovoltaics and hydropower form the backbone of low-emission (“green”) electricity generation
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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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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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work in state-of-the-art laboratories and clean rooms. The role involves working in a cryogenic laboratory environment and following specific clean room protocols Master`s degree in physics or electrical
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About the position Aluminium transition-metal nitrides have emerged as a family of new material that offers significantly enhanced piezoelectricity and beyond, empowering new acoustic and electrical
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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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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
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compliance with internal and external normative standards Write research papers for journals and conferences What you bring to the table Completed scientific university studies in the field of electrical
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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