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) programme and research school Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures
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the impact of processing techniques affect the (micro) structure as well as viscosity/texture of the model products. To establish the relationship between these characteristics and characteristics of the meal
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School. DDLS uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and
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responsibilities will include investigating the structural and biophysical properties of miniaturized tumor environment models. You will be responsible for fabricating these systems using both cleanroom-based and
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team of researchers in an European project. As a main topic, you will perform your research in one of these areas: -Data model translation, to enable the automatization of the engineering process
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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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Health Research and Policy-Work on Post-Covid-19 Syndrome ’ . Specifically, you will be working in the subproject ‘A Novel Model for Policy-Work’. One of the aims of this subproject is to examine what is
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training methods and model structures that can learn to master new situations without forgetting previously learned knowledge to an excessive extent. Such models, which perform continual learning
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theoretical research in nuclear physics, nanometer physics, quantum information, atomic physics, and modeling of materials, with several collaborations internationally and within Lund University. Subject
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algorithms to detect complex structural variants in humans using long DNA sequencing reads. A structural variant (SV) is a large-scale alteration in the genome that involves rearranged, deleted, or inserted