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methods in applied mathematics and computational modeling, this specific project aims to uncover new insights into how blood cells form in both healthy and disease states. A key objective is to model
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microtumor models. This work addresses a critical knowledge gap in cancer immunobiology and supports the development of more accurate disease models. Duties The main duty for a doctoral student is to devote
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vision, machine learning, deep learning and neural networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid
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analysis or predictive modeling of pathogen biology or host-microbe systems for which multidimensional, genome scale experimental data are now available, or it may use population scale genetic, clinical
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networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid academic background with thorough computational and
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documented international research experience, a demonstrated potential for creativity and a high degree of excellence in the field, for example in computational biology, mathematical modelling and simulations
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use the data to train deep learning models of cancer. This allows us to identify systems-level mechanisms that can be used to uncover new biomarkers, drug targets, and paths to drug resistance. We
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immunostaining of tissues and develops various tools for bioimage analysis, mostly using machine learning and AI-based models. We are now looking for a research engineer for the HPA team. As a research engineer in