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Experience with PyTorch/TensorFlow for computer vision tasks Track record of publications in relevant research fields Desirable criteria Multi-modal image analysis expertise Real-time detection and
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for the successful candidate to have considerable experience in some of the following areas: plant science, plant-microbiota interactions, microbiology, plant nutrition. A track record of publishing research is
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applicant should hold or be near the completion of doctoral studies into hypersonic flows or numerical methods or hold equivalent professional experience. The ideal applicant should have a clear track record
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/TensorFlow for computer vision tasks Track record of publications in relevant research fields Desirable criteria Multi-modal image analysis expertise Real-time detection and segmentation methods for clinical
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& resource management skills. A track record of quality research outputs, ideally through practice-based methods. Strong collaborative and interpersonal skills, with flexibility & confidence to work across
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, microscopy, flow cytometry and quantitative real-time PCR. You will have a strong track record of writing papers as evidenced by publications or submitted manuscripts in scientific journals, and have evidence
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are looking for a highly motivated and enthusiastic candidate with a PhD in Physics, Chemistry, Materials Science, Engineering, Chemical Engineering or a related area. A proven track record of scientific
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Experience interviewing victims-survivors of human rights violations and coding qualitative evidence A track record of publications Strong qualitative research and analysis skills Strong oral and written
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both institutions and industry partners. About the Project You will join FabricFlow – an innovative AI-powered ecosystem that revolutionises how fabrics are tracked and managed in the fashion industry
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an established track record in international collaboration and EU-funded projects, and maintains close links with leading academic and professional partners worldwide. The position is based in the Department