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theory, and machine learning to quantify and understand cancer biology. We are seeking a highly motivated Postdoctoral Researcher to develop new computational methods for the analysis and interpretation
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, a large initiative funded by the Danish Ministry of Foreign Affairs and managed by Danida Fellowship Council. Ethio-Nature aims to optimize the use of machine learning and remote sensing to site
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the ultimate goal to map and model human cell lineage dynamics across development, disease and aging at multiple levels of biological systems by integrating single-cell multi-omics and artificial intelligence
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and explainable hybrid Artificial Intelligence, i.e., the mix of formal knowledge representation and reasoning with sub-symbolic data-driven machine learning approaches, to work on car-driver digital
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in combination with computational biology approaches to generate comprehensive models of gene regulation during development and diseases such as cancer and neurodevelopmental disorders. To learn more
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and analysis. Data analysis and interpretation, including theoretical modelling. Establishing structure-property relationships and pushing the frontiers of the field. Collaborating nationally and
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European Lab for Learning & Intelligent Systems (ML/AI). Cell engineering for cancer and immune diseases (Bock Lab ). Development of innovative technologies for biomedical research, for example building upon
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this date. Job description Recent improvements in machine learning have dramatically improved the accessibility of de novo protein design. In this project, we seek to exploit these developments to interrogate
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, their interactions with hosts and the environment, and how they are transmitted through populations. Research will have a strong focus on computational analysis or predictive modeling of pathogen biology or host
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-doctoral research contract in Modeling and Engineering Risk and Complexity (MERC) - CUP F66E25000020006- • n.1 post-doctoral research contract inArcheologia e Culture del Mediterraneo Antico. Ricerca Storica