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efficient than digital computer and previous experimental implementations. This work is both experimental, numerical and theoretical in nature. You will be selected by the Applied Physics research group
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method, can engineer thousands of defined mutations in parallel in a single test tube in yeast. Strains are tagged by DNA barcodes, allowing to efficiently track mutations in cell populations during
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method, can engineer thousands of defined mutations in parallel in a single test tube in yeast. Strains are tagged by DNA barcodes, allowing to efficiently track mutations in cell populations during
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method, can engineer thousands of defined mutations in parallel in a single test tube in yeast. Strains are tagged by DNA barcodes, allowing to efficiently track mutations in cell populations during
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Project description We are a highly motivated international team of researchers at the Molecular Neurogenomics group (Jordanova Lab) and the Computational Neurobiology group (Malysheva Lab
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methods for these diseases. Approaches range from human genetics, genomics, protein biochemistry and neuronal and glial cell biology to integrative systems and computational biology. Models include yeast
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. Strong knowledge of quantitative and/or computational research methods, ideally in econometric analysis or optimization and simulation models. Preferable knowledge in Python and STATA. A collaborative team
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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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(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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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