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, molecular dynamics, and machine learning, to model battery electrolyte and solid electrolyte interphase (SEI), while collaborating with experimentalists. Qualifications • Ph.D. in Computational Materials
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advertisement About the position Integreat – Norwegian Centre for Knowledge-driven Machine Learning at University of Oslo is looking for a candidate for a postdoctoral project in ethics and AI. Starting date as
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, computational, and machine learning/AI methods, with a particular emphasis on deep learning approaches improve our understanding and prediction of infectious disease dynamics. Projects are also strongly grounded
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collaboration with industry partners. This work will apply optimal control theory, including machine-learning algorithms and Bayesian estimation, to coherent control of nitrogen-vacancy centers in diamond
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to apply advanced AI models in areas such as catalyst design, multi-scale modeling, and spectroscopic analysis. The Research Fellow will take on a significant role in machine learning theoretical energy
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, engineering, finance, and health. Key Responsibilities: To perform the pioneer research in AI for climate transformation. To further develop data-driven and machine learning tasks for fighting climate changes
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models using frameworks such as PyTorch and TensorFlow. Research experience in medical image analysis using deep learning algorithms. Strong track record in machine learning, computer vision, and medical
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both the NCRC in Kannapolis and UNC Charlotte in Charlotte. Experience in yeast genomics, RNA-sequencing, bioinformatics, or machine learning is preferred. Departmental Preferred Experience, Skills
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written and verbal communication skills regarding research results. Preferred Qualifications: Experience with deep/graph neural networks and active involvement in data science and machine learning projects
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methods to economic and environmental problems; Knowledge of STATA, R, Python and/or other relevant programming skills for undertaking applied analysis (e.g. machine learning) and handling large