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environments, e.g., Python, R, Microsoft Azure AI Studio, RapidMiner, Dataiku, etc. Methodological and statistical competencies (e.g., for analytics) Experience with cloud platforms such as Amazon Web Services
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with cloud platforms such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure German language proficiency at the A2 level according to the CEFR; English language proficiency
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The LIT - Leibniz Institute for Immunotherapy (foundation under civil law) (https://lit.eu/ ) – is a biomedical research centre focusing on translational immunology in the fields of cancer
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Your Job: Aerosol particles act as ice nucleating particles, providing surface for water vapour to deposit and freeze into ice particles. Formation of cirrus clouds and subsequent sedimentation
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 3 months ago
"Cloud physics" (f/d/m/x) Background With the project Deepcloud, we will use the machine-learning revolution to better understand clouds and their role in the climate system. We aim to train a deep
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, including fine-tuning techniques, RAG, and agentic workflows. Knowledge of wireless network, including WiFi, O-RAN, vRAN, and edge/cloud computing. Excellent programming skills in Python and popular
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 3 months ago
deep learning (x/f/d/m) Background With the project Deepcloud, we will leverage the machine-learning revolution to understand clouds and their role in the climate system. We aim to train a deep learning
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notebooks, and cloud-based research workflows for experimental-thin film photovoltaics research. We are looking for one motivated colleague to join our interdisciplinary team. Job description: scientific
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particles. Formation of cirrus clouds and subsequent sedimentation of ice crystals can dehydrate air in the upper troposphere and lower stratosphere (UTLS) region, thereby influencing the water vapor budget
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., food processing, bioconversion and fermentation processes) Self-supervised learning for multimodal sensor data (e.g., spectroscopy, hyperspectral imaging, 3D point clouds, and other high-dimensional data