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supporting documentation, proven experience in all of the following areas: Computer vision and video processing (ingestion, ROI, 2D/3D keypoints, heatmaps); Deep learning and temporal modelling (CNNs
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healthcare challenges, particularly in varies areas related to allied health, nursing and community health. Conceptualize, design and implement innovative projects based on deep understanding of healthcare
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intelligence. Strong knowledge and research outputs in AI, particularly in the field of deep learning, knowledge representation and reasoning, or neuro-symbolic AI. Proven commitment to proactively keeping up
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for structural biology. This project sits at the intersection of X-ray scattering and deep learning, aimed at integrating experimental data to predict protein ensemble structures. As an Empire AI-funded fellow
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of Applied Learning, the Singapore Institute of Technology (SIT) works closely with industry partners to deliver translational, impact-driven research. This role supports applied food processing
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), it must be equiva-lent to a master in the Norwegian educational system Documented proficiency in scientific programming (e.g., Python) Documented proficiency in deep learning frameworks (e.g., PyTorch
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with causal machine learning, ensemble methods, and deep learning
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Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL), particularly in Natural Language Processing (NLP) and Computer Vision (CV) Familiarity with genomic and bioinformatic databases
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CW and pulsed laser systems, spectrometers, high-resolution cameras, and delicate optical components are desirable Expertise in advanced data analysis techniques (Machine learning and Deep learning