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Nanomaterials that detect protein-structural changes Nano-optical devices for protein-signal sensing AI algorithms for protein structure and dynamics prediction Outstanding Postdoctoral Training Strategy
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sequencing and synthesis to design useful cell behaviors. The scope of this project is to combine multi-gene control technology and computer algorithms to develop a foundational discovery platform for future
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, for enhancing light trapping in nanostructured thin-film solar cells. Your role will focus on developing and applying large-scale electromagnetic simulations to identify optimal nanostructured light-trapping
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attacks Develop and implement ML algorithms to identify vulnerabilities and predict potential threats in supply chain systems Prepare project deliverables and disseminate results through high-quality
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is to investigate which antigen specificities are enriched in cell subpopulations, depending on the underlying neurological disease. The project will use high-throughput data to develop and apply
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data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms to understand
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skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and
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efficient decoding algorithms" supported by the Luxembourg National Research Fund (FNR). The APSIA Group is seeking a highly qualified post-doctoral researcher for this project. For further information, you
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disease into specific subclasses. You will develop AI algorithms to train models that predict if individuals (from which we create circuits) are prone to develop disease and to identify conditions that have
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develop and apply advanced preclinical model systems in lymphoma—including organoids, patient-derived xenografts (PDX), and humanized mouse models—to enable functional genomic approaches and the testing