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network inference and modeling, machine learning and deep learning. Experience in working with Arabidopsis and plant genome data is a strong plus. The position is expected to continue for multiple years
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assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu Employment Requirements Any offer of employment
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environment within the Physical Vision Group (PVG, https://physicalvision.github.io/ ). This will involve closely collaborating with faculty, postdoctoral researchers, and PhD students, bridging foundational
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at Carnegie Mellon University invites applications for a postdoctoral researcher to lead projects at the interface of computational chemistry, machine learning, reaction mechanism elucidation, and automated
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Łukasiewicz Research Network – PORT Polish Center for Technology Development | Poland | about 2 months ago
. The candidate will join ongoing projects in our team and perform mathematical/computational modeling. The topics include (1) constructing deep learning-based models to predict the molecular microenvironments
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cryosphere and is involved in various high-level research projects and centers. (See for instance http://www.mn.uio.no/geo/english/about/organisation/geohyd and https://www.mn.uio.no/geo/english/research
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conferences (e.g., NeurIPS, ICML, ACL, EMNLP, etc.). Proficiency in programming languages such as Python, and experience with deep learning frameworks like TensorFlow, PyTorch, or JAX. In-depth understanding
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economic, energy efficiency, and environmental performance metrics. Utilize reinforcement learning (RL) and deep reinforcement learning (DRL) for autonomous process management, dynamic resource distribution
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, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with causal machine learning, ensemble methods, and deep learning
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. Experience with deep learning and programming, preferably in Python, are required and should be evident from your academic track record, including the (online) courses you've followed, your publications