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research experience to include: Experience developing novel deep learning methodologies (e.g. transformer models, Convolutional Neural Networks, Auto-encoder models, or LSTM networks). Demonstrable ability
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machine learning applications. Acquisition, processing, and analysis of remote sensing imagery. Proficiency with GIS methods, applications, and visualization. Prior experience engaging with stakeholders and
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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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, seminars, and workshops. Translate findings for diverse audiences while maintaining scientific rigor. Qualifications: PhD in artificial intelligence, machine learning, cardiovascular medicine, genomics, or a
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participate in democracy, our centre tackles the promise and peril of hybrid intelligence—human and machine working and learning together. AI LEARN’s mission is to establish an internationally leading
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the future of automobile manufacturing. The Hyundai-NTU-A*STAR Corporate Lab invites applications for the position of Research Fellow. Key Responsibilities: Research & Development of advanced innovative
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calculations; Experience with developing, training, and optimizing neural networks or other machine learning models. For this position we are targeting a salary corresponding to Level 4 Spine Point 28 - 30
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researcher to help us deliver it. By combining coherent Raman scattering with machine-learning models trained on plant mutants, the project will shed new light on the cellular-level biochemistry that governs
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for imaging Apply for this job See advertisement About the position Position as PhD Research Fellow in machine learning available at Department for Informatics with the research group Digital Signal Processing
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Area: Computer Science 2. Admission Requirements: Graduates (Licenciatura) in computer engineering or related area, with experience in Machine Learning/Deep Learning methods/techniques. 3. Project