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, bioinformatics, aging biology, epidimological data and AI-driven systems modeling. The successful candidate will develop and apply computational and machine learning approaches to decode the molecular and
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employ cutting-edge single-cell and spatial omics technologies with bioinformatics and machine learning to decipher principles of gene regulation underlying cell identity and its disruption in human
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project. The research will bridge both established and emerging technical expertise within the section, encompassing areas such as FPGA and neuromorphic computing, Edge AI, machine learning, power
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considerations. Experience working with machine learning methods for control, perception, or decision-making in physical systems is an advantage. Knowledge of or a passion for sustainable computing
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Monitoring (LTVEM) in the hospital for management and diagnosis of epilepsy. The technology is built on brain computer interfaces equipped with a Spiking Neural Network (SNN) and aims at early detection
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in ion transport and (2) using machine learning methods to design protein binders. The incoming postdoc will have the opportunity to mould the project to a significant degree. The candidate should have
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related field. Strong software development and programming skills, with experience in designing and implementing complex software systems. Research experience in artificial intelligence and/or machine