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of core algorithms for image processing and computer vision based on deep learning and traditional algorithms; including but not limited to image recognition, detection, segmentation, generation
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hypotheses. The candidate will apply machine learning models to clinical and omics data for classification tasks. We are looking for highly motivated and organized candidates with good communication skills
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parameters affect material properties and functional performance, and interacting with machine-learning and modelling teams to translate experimental results into predictive datasets. Preparing reproducible
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Research Engineer - Tools developer for LSQUANT platform (Theoretical and Computational Nanoscience)
Personal Competences: Demonstrated competitive ability in using DFT simulations, and machine learning techniques and DFT. Demonstrated strong coding skills and a passion for UX/UI design. Summary
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of artificial intelligence (AI) and biomedical engineering. Research directions include deep learning, natural language processing, brain–computer interfaces, and their applications in disease prediction, drug
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to provide internal operational guidance and advanced tools that accelerate the adoption and development of machine learning (ML) methods across the centre. Its mission is supported by a set of strategic lines
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to support future project maintenance. Agile methodologies: Actively participate in team ceremonies (Daily Stand-ups, Sprint Planning, Retrospectives). Requirements: Bachelor's Degree in Computer Engineering
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commitment to fostering a diverse and inclusive community in the practice and teaching of science. The successful candidates will be expected to have excellent academic achievements, teach graduate and
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) Competences Highly developed organizational skills Strong collaborative skills, proactive attitude, and eagerness to learn and develop new technical expertise The Offer – Working Conditions Contract duration
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Cluster hire of PIs and postdocs in the fields of evolution, biodiversity conservation and ecology, genetics, neuroscience, brain-computer interface, human disease mechanisms and Interdisciplinary