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algorithms to compute similarity between interaction interfaces across millions of comparisons. This hinders identification of novel modes of protein binding, i.e. those predicted by AlphaFold, and it hinders
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straightens the fingers but does not treat the underlying biology; recurrence is common and repeat operations carry escalating risks to hand function. With genetic risk variants now linked to the disorder
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will work in an interdisciplinary environment at the TU/e Laboratory of Chemical Biology and the Expertise Center Clinical Chemistry Eindhoven (ECCCE), a collaboration between TU/e, Catharina Hospital
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-driven proteomic. Who are we looking for? A motivated researcher with strong programming skills and knowledge of machine learning algorithms, bioinformatics, proteomics, and molecular biology, keen to
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for Biomarker Discovery: Develop and fine-tune machine learning algorithms for biomarker discovery, cancer classification, and exploring omics features. Collaborative Research: Work in a multidisciplinary setting
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theory to unlock the efficiency of neuromorphic compute in multi-timescale processing. Job description Neuromorphic computing promises new energy efficiency records by taking inspiration from biology
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Job Description If you are curious and proactive scientist with expertise and interest in computational biology and data science, and you are looking to make a difference working on projects
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and Saeys teams. In this research project you will develop and apply algorithms to link clinical phenotypes of metastasis to molecular phenotypes in mouse models. It is known that metastases exhibit
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and Saeys teams. In this research project you will develop and apply algorithms to link clinical phenotypes of metastasis to molecular phenotypes in mouse models. It is known that metastases exhibit
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new brain stimulation methods, you will contribute to developing closed-loop algorithms for regulating brain dynamics with clinical applications in epilepsy and psychiatric disorders. Number of awards