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research, data science, cognitive science, or related disciplines who are eager to engage deeply in the Institute’s research activities in empirical education. We especially welcome applications from
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hearing loss. However, current neural devices are large, complex, and invasive, and are therefore used by only a fraction of people who could benefit from them. The goal of NANeurO is to design new
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science, automation science, or a related field, and convincing expertise in robotic hardware. Experience with machine learning and large language models is highly desirable. Prior experience in a biological setting
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, probabilistic models Representation learning, self-supervised learning, foundation models Data analysis, non-linear statistics, knowledge management Your profile PhD in Computer Science, Bioinformatics
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-08187-1 Your Profile: Master and PhD in biology, genomics or bioinformatics Strong background in data science or machine learning (deep learning, statistical modeling, or large-scale data analysis a plus
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integrate large-scale sequence and RNA-seq data from internal and public resources. You build a reference library of predictive regulatory motifs. You use network analysis and random-forest approaches
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at large scale facilities Establishment of cooperation projects with energy-related institutes at Forschungszentrum Jülich Initiating grant applications Supervision of MSc and BSc students Presentation
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European sea basins over decadal timescales, due to coastal darkening (COD) and artificial light at night (ALAN), and will determine drivers, sources and impacts of these changes at both large and small
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us We are TUM’s unique Pathology AI lab developing new machine learning (ML) methods for automatically analyzing digital pathology data and related medical data. Such methods include the automatic
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-reconstructions and observations, low-order data assimilation, or deep neural networks. A quantification of the impact of mesoscale and submesocale features is also expected. At a later stage, the successful