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in empirical analysis using econometric, machine-learning, and language-modeling techniques. Conducting literature reviews and synthesizing existing academic research to support ongoing projects
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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qualifications will strengthen the application: Experience with AI or machine learning applied to environmental systems Experience with coastal circulation modelling tools (e.g., Delft3D, MIKE, ROMS, FVCOM
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will focus on developing efficient foundation models to medical image analysis. Foundation models offer a scalable and adaptable solution for medical image analysis by learning generalizable
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accelerated AI, machine learning, and robotics algorithms with a strong focus on computational efficiency, memory reduction, and energy-aware deployment. The role targets foundation models, including large
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 13 days ago
). Experience in machine learning methods, including data preprocessing, model selection, and performance evaluation. Familiarity with programming languages commonly used in these domains (e.g., Python, MATLAB
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Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Research Fellow in Machine Learning for Computational Pathology, Medical Imaging, and Clinical Text Analysis Department Bashashati
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for light–matter interaction in hyperuniform disordered plasmonic structures, including electromagnetic modelling, optimisation of metal–dielectric–metal resonators, and physics-informed machine-learning
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machine learning methods as well as in biological data analysis are needed for the position. The postdoctoral researcher will play a leading role in this research, including methods development, data
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reproducible analysis workflows Familiarity with computational models of vision and machine learning methods (for example CNNs, deep generative models, encoding models) is preferred but not required Ability