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diverse backgrounds (e.g., economics, computer science, information systems, engineering, etc.), united in pursuit of sustainable solutions that positively impact and shape a low-carbon economy and society
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entanglement quality depending on experimental parameters, such as speed and efficiency. This will give a holistic overview of the performance of these colour centres, such that they can be operated at the ideal
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Applications should include: Curriculum Vitae Cover letter Early application is highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system. Applications by Email will not be considered. The University of Luxembourg is committed to...
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and entrepreneurship in all areas · Personalized learning programme to foster our staff’s soft and technical skills · Multicultural and international work environment with more than 50
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the synthesis of powders and thin films with the aim to investigate their fundamental opto-electronic properties using state of the art instrumentation as well as fabricate functioning demonstrator devices
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relevant state-of-the-art technologies. S/He will benefit from an active seminar program, international conference attendances, opportunities for professional growth. The project will be carried out in
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· An environment encouraging curiosity, innovation and entrepreneurship in all areas · Personalized learning programme to foster our staff’s soft and technical skills · Multicultural and international
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of computer science, cryptography. All positions are fully funded for up to 4 years. Candidates should have (at the beginning of the contract but not necessarily at the time of application) a Master's degree in
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research the Growing schools; Growing futures initiative, thereby contributing to the research program of the SciTeach Center team, led by Prof. Dr. Christina Siry. The PhD candidate will engage in
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Parkinson’s Disease, or markers of brain structure and functioning, depending on the dataset. To do this, knowledge or willingness to be trained in advanced statistical modelling, ideally with an interest in