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, Reliability and Trust (SnT) at the University of Luxembourg is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services. We play an instrumental role
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2025 - 23:59 (UTC) Type of Contract To be defined Job Status Part-time Offer Starting Date 1 Feb 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference
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, Reliability and Trust (SnT) at the University of Luxembourg is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services. We play an instrumental role
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that mimick human striatal function and we are using these systems to study the mechanisms of Parkinson’s disease. The system, that involves a high density multielectrode array enables us to measure single
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that mimick human striatal function and we are using these systems to study the mechanisms of Parkinson’s disease. The system, that involves a high density multielectrode array enables us to measure single
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, conduct pioneering scientific research and play an important service-providing role in society. We are one of the largest, most international and most innovative employers in the region. With more than 6000
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of synthetic promoters in planta. You will unravel the cis-regulatory code controlling context-dependent gene expression and use this information to edit natural promoters. You will work very closely together
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training data. You will unravel the cis-regulatory code controlling context-dependent gene expression and use this information to design synthetic promoters. You will train and evaluate predictive models in
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offer an innovative academic education to more than 20000 students, conduct pioneering scientific research and play an important service-providing role in society. We are one of the largest, most
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electrophysiology to translational models, including animal studies and analyses of human tissue samples. This full-stack methodology enables us to directly link molecular channel function with disease phenotypes