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particular by employing advanced methods from the field of artificial intelligence (AI) and its subfield machine learning (ML). Where to apply E-mail career@lec.tugraz.at Requirements Research FieldEngineering
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Biological Insights in Preclinical Glioma ModelsMulti-modal machine learning for predicting Glioma progressionHealthAEye: Deep Learning for Retinal Image Analysis and Disease Monitoring *Life Sciences:Germs
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leveraging advanced computer vision and deep learning-based pose estimation from football match footage to analyze pre-injury biomechanical patterns and joint load dynamics. The research aims to create
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classical and quantum mechanics, and machine learning, will be employed alongside the development of precise enzymatic assays and high-throughput robotic platforms to deliver novel enzyme activities
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process, identification of parameters, variational modeling, and generative machine learning methods; see https://imsc.uni-graz.at/mr-dynamo for further details. As part of this research effort, we invite
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sequencing, ATAC-seq, CHIP-seq, analysis: RNA velocity, Scenic, scFates) Excellent technical skills: confident use of one computer programming/scripting language (R, Python), competent in working in a Linus
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electromagnetic simulations is an advantage. For topics 4-5: prior experience in numerical simulations, applied mathematics and/or machine learning is an advantage. Interest and enthusiasm in research Excellent
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sequencing, ATAC-seq, CHIP-seq, analysis: RNA velocity, Scenic, scFates) Excellent technical skills: confident use of one computer programming/scripting language (R, Python), competent in working in a Linus
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and software development of the data acquisition system Optional: contributions to the setup of the new cryolab Optional: tasks may include methods of machine learning Where to apply E-mail
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of artificial intelligence and machine learning tools Very good knowledge of English and German Independent and conscientious way of working and enjoy working on application-orientated industrial projects as