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the following activities to collect the experimental data necessary for model development: Lab-scale fermentation experiments at various scales and with different setups (batch, fed-batch, and continuous modes
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stakeholders. Ability to manage in a scientific environment with in depth knowledge of the different models of research operations while enhancing a collaborative approach. Knowledge of the National Research
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external stakeholders. Ability to manage in a scientific environment with in depth knowledge of the different models of research operations while enhancing a collaborative approach. Knowledge of the National
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are needed to prevent infections with bacterial enteropathogens and AMR. Our previous research showed that there are differences in the E coli colonization of infants’ microbiome between LMIC vs. high-income
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therapies against glioblastoma. The PhD project will be conducted within the framework of the project Glioblastoma Blood-Brain Barrier Integrated Model for T-Cell Therapies (GBBRAIN-T). This fellowship is
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) solutions, multimodal signal processing, and digital biomarkers for accessible sleep monitoring in adult and pediatric populations with different health conditions. The aim of the project is to develop new
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when using closed, proprietary models, where model weights, training data, and internal representations are inaccessible. The PhD project will therefore investigate how trustworthy agentic AI systems can
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sensitivity, on resistance evolution. As model pathogen, we will focus on UTI E. coli and/or lung-infecting Pseudomonas aeruginosa. As a general reference, check out the group’s publications on AMR evolution
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systems, or continuous-time and discrete-time LTI systems theory is a plus. Experience with mathematical modeling, optimization, numerical computation, algorithm development, or machine learning. Prior
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datasets with different configurations (e.g., number of channels, sampling frequency and resolution). To leverage large-scale self-supervised learning to train models on unlabeled EEG data, reducing reliance