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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
solid academic background in polymer synthesis and electrochemistry. The candidates should be self-motivated to explore new areas of studies including AI related and machine learning fields, have evidence
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techniques such as causal machine learning and multi-layer network analysis, the project generates original knowledge on causes of rule of law weakening and the impact on socio-economic outcomes such as
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Karttunen, and Prof. Kari Laasonen, who will supervise the postdoc positions advertised here. We are seeking candidates with expertise in one or more of these areas: Machine-learning interatomic potentials
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, for event reconstruction and classification, including potentially machine learning/AI Interpretation in suitable theoretical models Contribution to software activities that are required for wider use by DESY
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of Virginia (UVA) School of Medicine is seeking to fill Postdoctoral Researcher positions in computational biology and machine learning. The lab develops modern machine learning, generative modeling, and
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is to be the “EO innovation hub” connecting EO with a growing ecosystem of disruptive and transformative innovations such as AI, machine learning, quantum computing, edge computing, metamaterials and
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, western blot, qPCR, IHC, ELISA Required License/Registration/Certification N/A Physical Requirements ☐Sitting at computer work station for long periods of time ☒Standing for long periods of time ☐Risk of
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. Python, Julia, C++, R); experience with sequencing (NGS) data, geometry or graph algorithms, statistical inference or machine learning; error-correcting codes or information theory; molecular modelling
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measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with modern deep learning frameworks (PyTorch, JAX, or equivalent). Have
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candidate will play an active role in analyzing LZ data, with opportunities to improve simulation models used in rare-event searches, develop machine learning methods for background rejection, and place