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floods—in mountain catchments. The goal is to understand long-term changes in runoff regimes and flood hazards by combining climate-driven (glacier-)hydrological modelling with reconstructions of past
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26 Aug 2025 Job Information Organisation/Company INESC ID Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Country Portugal
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models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly
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Oct 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 36 Offer Starting Date 1 Nov 2025 Is the job funded through the EU Research Framework Programme? Not funded by a EU
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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Australian National University | Canberra, Australian Capital Territory | Australia | about 6 hours ago
, attention-based models, and multi-modal learning approaches—to model RNA-mediated regulatory mechanisms and their dynamic interactions in disease. The position is part of an NHMRC Ideas Grant project
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Type of Contract: Full time - Funding limited for 34 months The postdoctoral research fellow will support the delivery of a variety of critical research tasks to deliver the JUST-Systems programme
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Energy Modelling and Simulation. The Dworkin group focuses primarily on numerical modelling, but also performs some experiments as needed for certain projects. The group currently has 2 Postdoctoral
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capacity around Water and Sanitation in low- and middle-income settings across Southeast Asia. This position offers a unique opportunity to contribute to field-based public health research and program
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algorithms and methods for adaptive and personalised feedback, modelling learning behaviours with sequence and deep learning methods, and generating interpretable insights through novel analytics and