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: Develop and implement machine learning algorithms for SOC and SOH estimation. Analyze large datasets from battery systems to improve model accuracy and performance. Conduct research on predictive analytics
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chemical discoveries for renewable energy, biomedicine, and other areas of societal importance. Coding and/or machine learning experiences are highly valued. Specific projects may involve developing
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multimodal deep learning models that integrate imaging and clinical data to personalize treatment and follow-up strategies. In the Netherlands, around 75% of patients with an abdominal aortic aneurysm (AAA
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delineation and improve the outcomes of SCC surgery. Job Responsibilities: As a PhD candidate, you'll focus on: Develop cutting-edge AI models: Train state-of-the-art deep learning models to segment SCC and
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Your profile The successful candidate will pursue a second book / "Habilitation" research project, teach courses, contribute to the Department's profile areas "Premodern History" and "History
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of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine learning “emulators” of multiple ice sheet and glacier models, based on large ensembles
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: Postdoctoral Position Location: Taipei, Taipei, Taiwan Subject Areas: Physics / Atomic Molecular and Optical Physics , Cold Atom Physics , Condensed Matter Physics , Machine Learning , Quantum Computing
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background in machine learning, predictive modeling, or applied AI Proficiency in Python and/or R; experience with libraries like scikit-learn, XGBoost, TensorFlow. -Experience working with real-world datasets
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Qualifications: Ability to quickly learn new things and work independently, open minded, along with previous research experience in the following areas. This includes experience with cell culture, microscopy and
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care. The Luo Lab in the Department of Biomedical Informatics and Medical Education has a Postdoctoral Scholar position open with a focus in machine learning. The postdoctoral scholar will work on topics