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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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applications and security of LLMs. For further information, please contact us at jerome.francois@uni.lu and lama.sleem@uni.lu
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., economics, business, technology), united in pursuit of sustainable solutions that positively impact and shape a low-carbon economy and society. For more information, please visit our website: www.uni.lu/snt
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. The project will involve significant collaboration, sample exchange, semiconductor and device characterisation. For more information on the position please contact Prof. Phil Dale phillip.dale@uni.lu or Prof
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promotes an inclusive culture. We encourage applications from individuals of all backgrounds and are dedicated to upholding equality and respect for our employees and students. General information: Contract
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extended from cloud solutions (such as OpenLLMetry), the research question is how to identify anomalies in collected information that can come from multiple AI services either invoked manually by users or by
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methods for causal inference in observational data, is strongly preferred. Using various existing large datasets with rich information for knowledge synthetisation and triangulation over the course of the
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The ERC Synergy project ALCEMIST (lcsoftmatter.com/alcemist ) challenges the conventional engineering mindset of using motors to drive passive structural components by developing innovative
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(e.g., economics, business, technology), united in pursuit of sustainable solutions that positively impact and shape a low-carbon economy and society. For more information, please visit our website
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respect for our employees and students. General information: Contract Type: Fixed Term Contract 36 Month Work Hours: Full Time 40.0 Hours per Week Planned start date: October 2025 Location: Campus Belval