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Science, Electrical/Computer Engineering, or a related field by the start date, with a strong publication record in computer vision, multimodal learning, or vision–language models. We require hands-on expertise with
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artificial intelligence with a preferred focus on computer vision and medical image analysis. Preferred Qualifications: PhD in Medical Physics, Bioengineering, Biomedical Engineering, Physics, Computer
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Graph Machine Learning and Graph Data Management At Section for DATA, Department of Computer Science, Aalborg University, a postdoc position is available. The project is funded by a Novo Nordisk
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/biomechanical analysis, computer vision approaches to pose tracking from video, surface electromyography (EMG) recording and analysis, vocal recording and analysis, dataset preparation, time-series analysis
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. Collaborate on multidisciplinary projects involving high-throughput phenotyping platforms. Apply machine learning and deep learning techniques to improve image processing and trait prediction. Analyze large
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-based observations, physical algorithms, and machine learning models. Participate in field data collection and validation to support model accuracy. Publish research findings in peer-reviewed journals and
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22 Oct 2025 Job Information Organisation/Company Universite de Montpellier Department Human Resources Research Field Biological sciences Technology » Computer technology Researcher Profile
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computational physics, computational materials, and machine learning and artificial intelligence, using the DOE’s leadership class computing facilities. This position will utilize methods such as finite elements
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, the Frontier supercomputer, and collaborate with experts in machine learning, optimization, electric grid analytics, and image science. The successful candidate will design and implement differential privacy
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computer science, or a field related to computational sciences. Must have a strong background in computer vision, artificial intelligence (AI), and/or wireless networking and systems, and related fields. Preferred