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Field
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learning, deep learning, and large language models (LLMs), for the analysis of high-throughput multi-omics datasets (especially single-cell and spatial omics) and large textual corpora (e.g., scientific
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of gene regulatory networks in various cell types. The research will leverage a large in-house dataset from iCAN, complemented by publicly available data. These efforts aim to uncover in more detail
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of innovative mass spectrometry-based workflows and data evaluation tools. The developed metabolomic and exposomic tools will be applied to address pressing research questions at the edge of environmental/food
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include a PhD in Computer Science, Artificial Intelligence, Natural Language Processing, Human-Computer Interaction, or a closely related field. Candidates should have demonstrated expertise in Large
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within our portfolio of hypothesis-generating screening studies, a methodological portfolio where we identify signals of interest from real-world register data to guide the conduct of tailored studies. We
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, collect and analyze relevant data. Qualifications For this position, applicants must have a PhD in sociology or another discipline that is deemed relevant in relation to the research being conducted within
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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global supply chain logistics. While ML has the potential to transform both applied large-scale optimization and theoretical combinatorial optimization, algorithmic reasoning remains a significant
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) Analysis of the experimental data, ideally connecting to our machine learning tools Presentation of scientific results on conferences and in publications Requirements PhD degree in physics or chemistry, or
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-based solutions to societal challenges. We have a long-term involvement in applied and interdisciplinary research, big data and data science, artificial intelligence (AI), the Internet of Things (IoT