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the knowledge acquired during the PhD with team members and acquire new knowledge. - Engage with the Local team at LIPN and the wider national community working on proof theory, programming languages and
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The University of London The University of London is both the UK’s largest provider of international distance and online learning and the convenor of a federation of 17 renowned higher education
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acquire their fate and establish precise connectivity with target brain regions during development, and how these processes are altered by stress and pathology. To address these questions, the team combines
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, a novel spatial discovery proteomics concept that integrates microscopic cell phenotyping with deep-learning based image analysis and global MS-based proteomics. This unique method was recently
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Fund project TARGETWISE. The candidate will be responsible for conducting machine learning omics data analysis within the computational team. The details on responsibilities, obligations and rights
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on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural networks - Analyze
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applying machine learning and computational methods for protein design, in close integration with experimental enzymology and biocatalysis. The tasks include: Development and application of AI and machine
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than major Western European cities. Focus: 100% research, no teaching obligations. Funding: NCN SONATA BIS grant (> €1 million) — fully secured and active. Language: The lab operates entirely in English
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research. A good command of the English language is required. Considered as an advantage Experience in international research cooperation and international researcher mobility will be regarded as merits
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, Statistics, computational biology, related disciplines or equivalent. They should be self-driven, highly motivated, creative with excellent communication skills in written and spoken English and Cantonese