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applications. The successful candidate will collaborate with team members conducting wet lab experiments to characterise the structure–function relationships of lipid formulations of interest, as well as with
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and design nanostructures tailored for aerospace applications. About us The Division of Engineering Materials explores the relationship between technologically important materials and their properties
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skills in quantitative modelling and analysis Strong written and verbal communication skills in English The following experiences will strengthen your application: Master thesis involving life cycle
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no more than three years prior to the application deadline.* Perhaps you have a degree in biochemistry/biophycis and want to learn more about neuroscience and biology, or vice versa. Crossdisciplinary experience
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Computational Science, Software Engineering or Computational Physics. Experience in programming (python, C++, fortran...), data management and/or visualization is needed. Experiences in plasma physics is meriting
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field-based experimentation. The division contributes to knowledge development in electrical systems for renewables, vehicles, buildings, and industrial applications. Recent projects have addressed smart
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of neural networks and other symbolic techniques with applications ranging from mathematics to cognitive science, and often in cross-disciplinary collaborations. In this project the PhD student will work
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experiences will strengthen your application: Pedagogics, adult training, skills analysis Industrial automation, robotics, and applications of AI XR/AR/VR and augmenting technologies Ergonomics, workplace
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learning, and control is essential. Applicants should also demonstrate: High academic achievement in relevant undergraduate and graduate courses Proficiency in programming (C/C++, Python) and experience with
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RAM3 . The aim of the project is to enable the broad application of recycled aluminium in high-value products produced through mega-casting. The main goal of the PhD project is to develop high-throughput