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of precision fermentation or cell culture - Affinity towards technical tasks and bioprocess control - Advantageous: Experience in mathematic modeling, programming, CAD, microfluidic or bioreactor systems
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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requires a dedicated individual with extensive previous research experience, in murine transgenic models and hematology. We are looking for a talented individual to carry out exciting studies in
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scientists covering a broad range of expertise in photonics and electronics. The Project in Short The project focuses on developing numerical modeling and optimization tools to explore the information
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or compromised IoT devices by analysing encrypted traffic patterns, focusing on metadata, flow characteristics, and timing rather than decrypting payloads. The core challenge is creating features and models
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will also include evaluating and validating existing numerical models, ensuring their reliability in predicting real-world conditions. This project is supported by brand-new laboratory facilities
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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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, Applied Mathematics, or a related field. Strong foundation in computational modelling & numerical simulations The laboratory The Decision and Bayesian Computation (DBC) – Epiméthée (EPI) laboratory
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Program (PRR Workplan: (1) Numerical simulation of the behaviour of connections between prefabricated concrete walls using finite elements; (2) Case study analysis; (3) Processing and analysis of results