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Field
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of the art in informed machine learning methodologies applied to computer vision. Application and validation of the developed methodologies in imaging analysis cases in biology. Machine and deep learning
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applicant promises to work full time at SPST upon acceptance of the offer. Application Procedure: Applications should include curriculum vitae, a 3 pages statement of research interests and the names of three
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LevelBachelor Degree or equivalent Skills/Qualifications Programming in Python and use of AI/ML libraries (scikit-learn, pandas). Proficiency in video and image processing (OpenCV). Knowledge of deep learning
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simulation of scenarios with different materials and geometries. - Support the development and implementation of signal and image processing algorithms, including fast inversion techniques, FFT, and nonlinear
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in bioinformatics and artificial intelligence, applied to biomedical big data, including omics, clinical, and imaging data. - Develop and optimise bioinformatics pipelines for the processing and
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or settlement-scale analysis. Drone photogrammetry for urban and architectural analysis. Machine learning models for spatial classification or mapping from satellite images. LiDAR data processing and integration
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Technician contract until December 2026 to work in a multidisciplinary research project that combines photonics, neuroscience, molecular biology, in vitro and in vivo calcium imaging and MRI. The hosting group
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Dr Mara Dierssen. The position requires a candidate with previous experience in Bioinformatics. The candidate will process and analyse multi-omics datasets (eg. RNA-Seq, smallRNA-Seq, proteomics
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assisting with in-situ TEM measurements, facilitating cutting-edge research in sustainability and energy fields. Part of the project will also include the development of deep learning frameworks for TEM image
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, so that their information content is known, and using imaging and genetics to characterise how that information becomes represented within individual mammalian cells. Where to apply E-mail