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-analysis pipelines (statistics, mathematical modeling, and ML) for terabyte-scale 3D histology images, from preprocessing to analysis and validation. Handle and visualize large 3D microscopy datasets. Image
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on the topic assigned for each position. Requirements: outstanding university degree (typically M. Sc.) in Computer Science, Data Science, Statistics, Mathematics or another relevant field study with good GPA
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communication with strong methodological skills. The PhD position is part of the VIDI-funded project ‘Fueling the fire: How do social media contribute to polarization?’ (PI prof. dr. Sanne Kruikemeier) and is
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skills and knowledge for processing, preparing and statistically analyzing big data; The skills and knowledge for carrying out in depth empirical studies; Excellent research skills demonstrated by a Master
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experimentation with Asst. Prof. Eli N. Weinstein. Your goal will be to develop fundamental algorithmic techniques to overcome critical bottlenecks on data scale and quality, enabling scientists to gather vastly
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: TRR408-A7 Investigators: Prof. Dr. Ostap Okhrin, Chair of Econometrics and Statistics esp. in the Transport Sector and co-supervised by Prof. Dr. Kai Nagel, Chair of Transportation System
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in Information Systems. In the context of Prof. Fridgen's PayPal-FNR PEARL Research Grant and the FutureFinTech National Centre of Excellence in Research and Innovation, the successful candidate will
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Computer Science and Computer Engineering with specialisation in Information Systems. In the context of Prof. Fridgen's PayPal-FNR PEARL Research Grant and the FutureFinTech National Centre of Excellence in Research
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received after the review date will only be considered if the position has not yet been filled. Position description The Computational Medicine Research Group led by Prof. Pratik Shah at the University
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methods experience in the statistical analysis of research results or willingness to acquire such experience willingness to conduct a research stay for several month at another institute very good knowledge