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Machine Learning Integration Develop and implement machine learning algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC
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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
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, the work might involve implementing new algorithms in the SCT tool Supremica, which is developed by the Automation group. Main responsibilities Conduct research in collaboration with senior researchers and
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of Systems and Control, we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms
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viruses and individual cells to evolutionary biology and global biodiversity. Taking on research studies at the Department of Biology generally means focusing on a delimited part of the research area of
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with .root files and explore different event generators as well as machine learning tools and algorithms. The nature of LDMX as an international project will require you to work collaboratively in
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significant role in learning in AI by enabling cognitive agents to acquire actively knowledge and skills through interaction with their surrounding environment. Embodied AI requires tools, algorithms, and
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both academic research and industrial applications. In addition to theoretical research, the work might involve implementing new algorithms in the SCT tool Supremica, which is developed by the Automation
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. The successful candidate holds/or are about to receive a Master of Science degree in computer science, data science, or a related area, and have strong background in algorithmic design, data mining, machine
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knowledge in thermal energy storage, techno-economic analyses, and AI tools/algorithms is a merit. In addition to the above, there is also a mandatory requirement for English equivalent to English B/6