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photopolymerization of the precursor. The practical work will be complemented by fluid mechanics computer simulations, including solutions employing machine learning, and theoretical analysis using Leslie-Ericksen
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Pathogenesis in the age of the microbiome (MICRO-PATH; https://micro-path.uni.lu ) is a highly competitive, interdisciplinary, research-intensive PhD training programme, supported by the PRIDE
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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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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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diverse backgrounds (e.g., economics, engineering, computer science, information systems, etc.), united in pursuit of sustainable solutions that positively impact and shape a low-carbon economy and society
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Qualification: The candidate should possess a MSc. Degree or equivalent in Engineering, Computer Science, or related fields. Experience: The ideal candidate should have some knowledge and experience
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Qualification: Master in Computer Science and/or Cybersecurity or equivalent degrees with expertise in at least one of the above areas (dependability, real-time systems, operating systems
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As a part of this collaborative research programme, you will join as one of three PhD candidates working on interconnected projects in Quantum Optimisation, People-Centred Design (PCD
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We are looking for a doctoral candidate with a strong computational, engineering, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to
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an ambitious research program. It will utilize a data-driven approach to support decision-making for an optimal energy system, with specific focus on cost-effectiveness, emission reduction, and social