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project team on “Participatory Algorithmic Justice: A multi-sited ethnography to advance algorithmic justice through participatory design” (PARTIALJUSTICE) to examine issues of justice and participation in
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methods, machine learning algorithms, and prototypical systems controlling complex energy systems like buildings, electricity distribution grids and thermal systems for a sustainable future. These systems
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-learning algorithms Versatile data-science knowledge, including image and DNA sequences processing Programming skills in Python or other modern programming languages supporting AI and bioinformatics
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PostDoc in "Sustaining the keystone: Rethinking Antarctic krill fishery management under climate ...
CCAMLR. CCAMLR aims to manage this fishery sustainably, relying on ecosystem-based approaches incorporating data on predator population, ecosystem state, and krill biomass and distribution. The krill
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Max Planck Institute for Astronomy, Heidelberg | Heidelberg, Baden W rttemberg | Germany | about 1 month ago
) spectral energy distribution fitting, star-forming regions/nebulae analysis, photometry, region morphology and/or catalog generation are in particular encouraged to apply. Applicants (m/f/d) should have a
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Southeast Asia) are welcome. Your Future Tasks: Engage in interdisciplinary research focused on mantras and/as sound, and mantras as unequally distributed sounds. Publish your findings in peer-reviewed
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near-real-time forecast system for the Baltic Sea Generate high-resolution daily surface salinity maps for the Baltic Sea and validate them with available observational datasets Develop algorithms and
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of how hotspots in human and marine mammal presence are distributed in affected areas. Acoustic ship models will furthermore help to understand and gauge the acoustic footprint of ships in various types
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Research profile in machine learning (e.g. robustness, out-of-distribution/anomaly detection, fairness, explainability, uncertainty quantification) or AI applications in the healthcare domain Interest in
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to develop a 3D-generative algorithm for pharmaceutical drug design by using or combining novel machine learning approaches? How would you integrate machine learning, physics-based methods in an early-stage