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Field
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should hold a Master's degree in Computer Science, Artificial Intelligence, Computational Linguistics, Data Science, or a closely related field Solid background in machine learning and natural
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of Unix systems (GNU Linux) and keen to gain hands-on experience in Networks and systems Machine Learning knowledge is a plus Strong analytical and programming skills are required (Python, Matlab, Golang
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command of written and spoken English • Experience with qualitative research methods is an asset • Good knowledge of machine learning /data mining in science • Good programming skills in at least one
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of the suitability of the profile for the functions and tasks to be performed focuses on the candidate's experience in machine learning and COMSOL modelling of materials and devices. Note: These criteria will be
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projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome
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to prepare project reports and co-author research papers. The ideal candidate is expected to be working towards a PhD in Computer Engineering, Computer Science, Computer Systems Engineering, Electronic
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researchers, it is a globally respected institution that also has outstanding economic significance for the Rhine-Neckar metropolitan region. Research Assistant/PhD Position – Computer Architecture (f/m/d
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willing to work in a collaborative environment. Preference will be given to those with (i) strong background in quantitative methods, geospatial methods, AI and machine learning; (ii) experience in high
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publications and present them at well-known international conferences and workshops. Your profile M.Sc./M.Eng. Degree in telecommunication engineering, signal processing, machine learning or a closely related
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the rank of Research Assistant Professor in computational mathematics, machine learning, scientific computing, statistics, and related areas. The appointee is expected to conduct high-impact research