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A two-year postdoc position is available in the research group of Algorithmic Cheminformatics at the University of Southern Denmark (SDU). The position is in an exciting 6-year project supported by
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and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training
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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune
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Nanomaterials that detect protein-structural changes Nano-optical devices for protein-signal sensing AI algorithms for protein structure and dynamics prediction Outstanding Postdoctoral Training Strategy
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interdisciplinary teams to apply developed algorithms to real-world datasets and generate valuable biological insights. Perform integrative analyses of multidimensional datasets within the context of basic immunology
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efficient decoding algorithms" supported by the Luxembourg National Research Fund (FNR). The APSIA Group is seeking a highly qualified post-doctoral researcher for this project. For further information, you
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computational algorithms to enable regenerative cell therapies. Now, we are seeking a highly driven postdoctoral researcher to contribute to our ambitious mission. Division The Division of Biomolecular and
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. The most recent methodological research of the group includes algorithms for cell type deconvolution, high-resolution purification, and integration of single cell multi-omics data. This postdoctoral fellow
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data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms to understand
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advanced AI algorithms to optimize and understand the optical properties of light-trapping surfaces. (more information can be found in the following News post ). You will work closely with colleagues both