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of project results at international scientific conferences Curation and publishing of data collected in the framework of the project Supervision of students and research assistants in project-related tasks
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talented individuals passionate about AI, Human-Computer Interaction, Eye-Tracking, and their responsible applications. Ideal candidates will have: • An M.Sc. degree (or equivalent) in Computer Science, Game
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Germany Web: https://www.mpinat.mpg.de/grubmueller Social Media: https://bsky.app/profile/compbiophys.bsky.social www.mpinat.mpg.de/ Information pursuant to Article 13 DSGVO on the collection and processing
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to perform theoretical physics research at the interface of quantum information, condensed matter and high-energy physics. A strong background and interest in one or more of the following topics is desirable
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resilience and its change over time in the past (based on Earth observation data), present and future (based on Earth system model simulations for different future scenarios, e.g. using the CMIP6 ensemble and
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 3 hours ago
the structure from such data is challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine
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chronometabolic research Analysis and quantification of circadian rhythms by rhythm analysis software (Cosinor, JTC cycle, R etc.) Rhythm analysis in human 24-hour time series data and omics data Writing
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Researcher / Postdoc for molecular investigations on microbial ecology in deep-sea polymetallic n...
nodules) in combination with data on metabolic rates, and sediment biogeochemistry will form the basis of the work. Further sampling and measurements will take place in the CCZ as part of the project
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resilience and its change over time in the past (based on Earth observation data), present and future (based on Earth system model simulations for different future scenarios, e.g. using the CMIP6 ensemble and
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evaluation methods for vision models Design metrics to compare neural and behavioral data with computational predictions Collaborate with CRC groups on open, reproducible standards for model evaluation Mentor