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by beam (e.g. laser light, electrons) and plasma induced processing. LAMP provides full cycle technology development, starting from novel materials, deep understanding of the background physics of beam
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materials synthesis with synchrotron radiation, neutron scattering, spectroscopy and electroanalytical methods. A major research direction is the development of physical methods and models for the description
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, and selective forgetting, and translate these into training-recall-forgetting cycles on physical polymer films and bilayer actuators. Contribute to integrating learning materials into soft robotic
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physics-based and data-driven modeling and data-analysis skills (e.g. Python, MATLAB, or comparable tools) are an advantage High interest in interdisciplinary research Excellent communication skills and
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-impact scientific publications. Your profile Master’s degree in Materials Science, Chemistry, Chemical Engineering, Physics, Biophysics, Pharmaceutical Sciences, or a related field. Quantitative mindset
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candidate with a master's degree (or equivalent) preferably in physics, physical chemistry or materials science. Experience in surface science and hydrogen technology is of advantage. The ideal candidate has
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by beam (e.g. laser light, electrons) and plasma induced processing. LAMP provides full cycle technology development, starting from novel materials, deep understanding of the background physics of beam
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states. Your profile The position is suited for highly motivated students interested in experimental condensed matter physics, nanoscience, and quantum materials. Candidates should hold a Master’s degree
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systems developed in the SAM3 project in terms of process-structure-mechanical property-function relationships. The candidate will be enrolled as PhD student at the Doctoral School for Materials Science and
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motivated team player who thrives in a collaborative and interdisciplinary research environment. The ideal candidate possesses a PhD degree in chemistry or chemical engineering, materials science, physics