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total. In your project, you will do research on and apply machine learning techniques to make a real-world impact in academia and at financial institutions. A potential research topic is the design of
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cannot be overstated. Using the power of Machine Learning (ML) models, our project will examine financial investments and credit risk indicators. While these AI techniques have found widespread application
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for explainability, regulatory compliance, model abstractions, and human judgment. We will also examine technological challenges like digital twin environments, machine learning pipelines, and digital finance
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control systems. You have skills in data analytics/machine learning: proficiency in data processing, analysis, and interpretation to develop predictive models and optimize manufacturing processes. You have
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present research findings in top-tier conferences (e.g., Machine Learning, JMLR) and journals (e.g., NeurIPS, ICLR, ICML, IJCAI, AAMAS, ECMLPKDD). Collaborate with a international team of researchers and
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-based monitoring approach to characterize melt pool spatio-temporally as well as spectro-thermally, Develop algorithms for sensor fusion using Artificial Intelligence/Machine Learning concepts to optimize
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methods to scale up deep learning. Publish and present research findings in top-tier conferences (e.g., NeurIPS, ICLR, ICML, IJCAI, AAMAS, ECMLPKDD) and journals (e.g., Machine Learning, JMLR). Collaborate
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to staff position within a Research Infrastructure? No Offer Description The vacancy is focused on calibration in deep learning. Deep Neural Networks (DNNs) have demonstrated significant predictive
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in their work, facilitating the analysis of medical images and other data, for more rapid, comprehensive and accurate diagnosis, guidance of surgeries and more. Today, deep learning methods