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SPECIFICS Postdoctoral Scholar – Public Health Sciences Postdoctoral Scholar of Machine Learning and Statistical Genomics Description: The Department of Public Health Sciences is seeking postdoc scholars
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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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spectral imaging, lifetime data, or multi-channel image datasets. Solid background in chemometrics, machine learning, or deep learning, particularly for classification, clustering, or pattern recognition in
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. Applications are invited for a full-time Postdoctoral Researcher in development of plasmonic nanopore for single molecule sequencing by surface enhanced Raman spectroscopy (SERS) position under supervision by
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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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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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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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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
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experience with deep learning frameworks like TensorFlow, PyTorch, or JAX. In-depth understanding of transformer architectures, attention mechanisms, and fine tuning techniques for LLMs. Experience with time