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Field
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machines Machine Culture Ongoing work on social reinforcement learning and evolutionary optimization of social strategies Our aim is to advance the scientific knowledge of human-AI systems by understanding
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of machine learning and clinical oncology, with access to a large multimodal research dataset, substantial GPU resources, and a collaborative scientific environment. Your tasks Design and implement LLM-based
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Science in Earth Observation develops innovative signal processing and machine learning methods, and big data analytics solutions to extract highly accurate large-scale geo-information from big Earth
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Karlsruhe Institute of Technology - Institute of Applied Geosciences - Division of Geothermal Research | Karlsruhe, Baden W rttemberg | Germany | 3 months ago
seismology and signal processing. Strong programming skills (e.g. Python, MATLAB, C/C++). Proven experience in big data analysis and/or machine learning. Interest in geothermal applications. Enthusiasm
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or complementing traditional physics-based approaches by data-driven ones, using Machine-Learning (ML). Such approaches allow enormous gains of time, in a way that can be related to the astonishing efficiency
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learning-based surrogates for physical systems LLMs and scientific agents – large language models that autonomously reason, plan and execute scientific workflows AI for engineering design – LLM-driven agents
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machine learning-based model to map satellite retrievals to ground based air pollutant concentrations Conducting error assessment on the derived concentration data Implementing new observational data
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establish a research profile. Develop and execute innovative research projects. Develop, train, and evaluate modern machine-learning models on GPU/HPC infrastructure. Integrate AI methods with scientific
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directions include (but are not limited to) For AI in Biomedicine: Representation learning for complex biomedical data Large language models for patient records and multi-omics Generative AI for therapeutic
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molecule interaction modeling, polymer physics, and statistical inference to investigate RNA structure, function, transport, and regulatory mechanisms in health and disease. AI and Machine Learning for RNA