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aspects of predictive modeling. A Ph.D. in bioinformatics, genetics, statistics, computer science, or a comparably quantitative discipline (e.g., mathematics, physics), or comparable research experience
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different brain models (tree shrew, macaque, human neurotypical, schizophrenia patients) and levels of analyses (local- and large-scale circuits). This is a unique opportunity to learn about team science
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, key Arctic geological archives of past warmth and employ climate models to bring our current knowledge about a warm Arctic beyond the state-of-the-art. The major strength and aim of i2B
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, religion or ethnic background are encouraged to apply. As DTU works with research in critical technology, which is subject to special rules for security and export control, open-source background checks may
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vivo neuroscience experiments in rodent models of addiction. Design and conduct cutting-edge experiments, lead independent research projects, and contribute to collaborative, multidisciplinary studies
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SUMOylation, transcription factors, or chromatin dynamics. Expertise in machine learning or statistical modeling for biological data. Knowledge of enhancer-promoter interactions and 3D genome organization. All
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language models (LLMs) for educational purposes. Furthermore, the right candidate has a deep understanding of pedagogical research, with focus on how educational processes can be facilitated by AI. The role
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Computing (e.g., memristor modeling/simulation/manufacturing) and Edge AI related areas (e.g., AI algorithms, AI accelerator, VLSI). Background Investigation Statement: Prior to hiring, the final candidate(s
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predictions of economic and sociological models. Examples of current research projects include: long-term impacts of neighborhoods and place-based policies, the role of colleges and workforce training in upward
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models to simulate lifeless and inhabited worlds, and Developing disequilibrium-, redox-, and information-based metrics to understand and quantify the influence of life on planetary environments