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-scale screens to study fundamental principles in molecular and complex trait genetics using microbes as model systems. Our core technology MAGESTIC (https://doi.org/10.1038/nbt.4137 ), a CRISPR/Cas9-based
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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-scale screens to study fundamental principles in molecular and complex trait genetics using microbes as model systems. Our core technology MAGESTIC (https://doi.org/10.1038/nbt.4137 ), a CRISPR/Cas9-based
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the fundamental aspects of transcriptional control, this project also opens new avenues for the design of climate-resilient crops. Supported by single-cell profiling and predictive artificial intelligence models
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member's task is strongly intertwined with the tasks of the other team members. You will design, train and apply generative models that learn how to complete missing wedges in the reciprocal space of crystal
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datasets. Your focus will be on implementing and training generative models to decompose cylindrical projections. You will solve and refine the structures from the resulting decomposed data. You will map
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working on a third-party funded project funded by the Luxembourg National Research Fund (FNR) on 'Rule of Law Principles - which model for the Global South?' The project focusses on the transition
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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subteam, working closely with an experienced lab technician, two dedicated PhD students, and two postdoctoral researchers on a project focused on in vitro screening methods, including the use of organoids
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in January 2025. The overarching goal is to identify the key factors controlling microbe-mediated carbon storage in the ocean, with a focus on using model microbial systems in the lab. We specialize in