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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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risk factors. The main objective is to design and apply machine learning and deep learning methods to understand and investigate the functional behavior of gender-specific cancers. The work will include
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Number: 6861527 Postdoctoral Scholar Employee - Astrophysics - Department of Astronomy Position overview Salary range: The UC postdoc salary scales set the minimum pay determined by experience level at
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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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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
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | 3 months ago
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 Computing (HPC
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with a minimum of one year eligibility remaining. •Strong expertise in first-principles modeling or molecular simulations relevant to catalysis, and experience with machine learning models. •Deep
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on the circular economy. This role requires deep expertise in advanced survey methodologies, experimental design, and statistical modeling. The ideal candidate has a strong research publication record and
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(“overparameterized”) machine learning models, like probabilistic graphical models, deep neural networks, diffusion models, transformers, e.g. large language models, etc. SLT is based on the geometrical understanding