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discipline. Strong experience in numerical/computational modelling (e.g., FEM/multiphysics, wave propagation, computational mechanics). Evidence of scientific programming and good software/reproducibility
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intelligence, and multimodal learning. The main objective of this position is to develop novel generative AI methods for computer vision applications, with a particular focus on Diffusion Models and Vision
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high-resolution urban climate modelling within a nationally coordinated research program involving NEA, A*STAR, NTU and NUS and international collaborators. Qualifications Applicants must have a PhD
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, seeks to recruit a junior research scientist to develop AI-enabled healthcare applications. Key Responsibilities: Develop and fine-tune computer-vision models, instance segmentation, and retrieval-based
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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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algorithm development and system performance. Technical Focus Areas Computer Vision and Model Development: Design and train deep learning models for insect classification and morphological recognition
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) to develop 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
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experiments, and validation of computational models. Required Qualifications: A successful applicant must have a PhD in Civil Engineering, Engineering Mechanics, or Mechanical Engineering. Applicants
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Design of a simulation model for the cutting of metallic and non
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the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description ETECNIC is a technology company specialized in