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characterization in the context of mammalian cell line experiments Protein design and engineering Protein biochemistry and structural biology Cellular proteostasis Bioinformatics, statistics, and programming
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of Things), Wireless and Mobile Communications (e.g. IEEE 802.11, Bluetooth, etc.), Protocols (e.g., MAC, Network, and Transport). Mathematics: Statistical Learning, Stochastic Processes (e.g., Percolation
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Mathematics, Statistics, Physics, or other quantitative discipline Solid programming skills Fluency in both spoken and written English is mandatory Ideal Qualifications Experience with deep learning frameworks
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understanding of physiology, MATLAB and statistic skills, and advanced technical understanding Proactive and inquisitive personality, eager to exploring new approaches, self-motivated and team-oriented Excellent
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description In particular, this PhD research project examines: The socio-spatial vulnerability to hard densification of population groups living in older housing stock through statistical socio-spatial analysis
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Management, Business Administration, or a related field. Independence and high motivation for academic research in the group’s topics. Proficiency in empirical research methods, including statistics and data
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discourse and reduce hate speech. We work together with online newspapers and use social media data. Our research employs advanced statistical methods for causal inference and we develop state-of-the-art
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programming (e.g., Python, C++, or similar) Experience with signal processing, machine learning frameworks, or statistical modeling Academic Background: A Master’s degree in Computer Science, Electrical
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services. Develop your skills in spatial data analysis and statistics while working with diverse datasets to uncover important biophysical and socio-economic patterns. Be part of interdisciplinary