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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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Center for Advanced Systems Understanding, Helmholtz Center Dresden-Rossendorf | Germany | 3 months ago
environment Excellent programming skills in languages such as Python, C/C++ and CUDA Familiarity with modern deep learning frameworks like Tensorflow 2.x.x, PyTorch Mandatory experience with High-Performance
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Deep Learning libraries (e.g., Pytorch, Tensorflow, Keras) will be considered a significant advantage; Previous experience in image processing and\or computer vision will be considered an advantage
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in digital health, fitness, and rehabilitation. Preferred Qualifications Background in machine learning/deep learning is a plus. Equipment Utilized Physical Demands and Work Environment PHYSICAL
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from the areas of few-shot learning, continual learning and modular deep learning, as well as different LLM alignment frameworks, based on reinforcement learning and direct preference optimisation
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Experience Appropriate PhD in a related field. Preferred Qualifications Experience with machine learning and deep neural network techniques. Experience with wearable and sensors placed in the environment
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related to staff position within a Research Infrastructure? No Offer Description Description of the workplace Automatic Control is an exciting and broad subject, covering both deep mathematics and hands
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-Based Wildfire Smoke and Air Quality Monitoring; Deep Learning for Post-Wildfire Damage Assessment. PROFILE of the OFFICE OF POSTDOCTORAL AFFAIRS (OPA) The mission of the UNLV Office of Postdoctoral
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, Automation, Artificial Intelligence, Operations Research, or a related field. Solid research background and practical experience in one or more of the following areas: Reinforcement Learning / Deep
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or more of the following areas: Reinforcement Learning / Deep Reinforcement Learning Fine-tuning and Application of Large Language Models Time-Series Data Prediction and Modeling Intelligent Decision-Making