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, journalism, political science, sociology, law, economics, or computational social science, as well as an interest in how AI transforms the media and information ecosystem. The PhD student(s) will be embedded
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). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing provably powerful learning models for graphs will
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and routine methodologies for tech transfer to GMP operations Analyzing data and creating graphs using appropriate software (e.g., SoftMax Pro, Excel, Prism) and data visualization tools; writing
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monitoring allow personalised diagnosis and treatment. ENDOTRAIN will train a new generation of interdisciplinary experts who merge clinical endocrinology, AI, data science, engineering, ethics and law into
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of interdisciplinary experts who merge clinical endocrinology, AI, data science, engineering, ethics and law into an integrated field of digital endocrinology. The programme focuses on adrenal
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Collaborate with CCY researchers on ongoing projects and contribute to the development of new research initiatives Contribute to data analysis and data management Contribute to national and internationals
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research looking to map and understand evolution in ocean temperatures in the shelf seas around New Zealand with opportunities to work with sampling, data analysis and modelling aspects but with an emphasis
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(Administration) recruiting.leibniz-lsb(at)tum.de . We look forward to receiving your application! Data Protection Notice: As part of your application for a position at Leibniz-LSB@TUM, you will transmit personal
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experimental campaign to characterize its performance. You will be responsible for setting up a state-of-the-art data acquisition system to monitor temperatures, flow rates, and power consumption. Your
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Responsibilities • Lead data analysis and interpretation to produce reliable and well-supported findings. • Plan, execute, and troubleshoot research projects with attention to rigor and reproducibility. • Stay