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is expected to be open to combine both positivist and non-positivist approaches under the supervision of Carolin Ischen and Gijs Schumacher, both specialized in large-scale quantitative analysis and
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sciences, biomedical engineering, or psychology; good command of English (minimum B2 level); proficiency in using data analysis software (familiarity with Spike2 software is an additional asset); basic
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for the processing, analysis and interpretation of large volumes of scientific data, as well as to the integration of artificial intelligence-based tools into highly technologically complex research environments
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systems are generally ill-conditioned. The project sits at the intersection of classical numerical analysis, scientific machine learning and computational chemistry. Based on regularization techniques and
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and analysis of dedicated algorithms for training analog circuits directly from data. In this PhD project, you will develop a novel system-theoretic framework for learning in analog circuits and
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Infrastructure? No Offer Description The AITAX project aims to address the complexity and dynamics of modern tax regulations by developing a cutting-edge AI solution for automating the analysis and processing
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Infrastructure? No Offer Description The AITAX project aims to address the complexity and dynamics of modern tax regulations by developing a cutting-edge AI solution for automating the analysis and processing
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Infrastructure? No Offer Description The AITAX project aims to address the complexity and dynamics of modern tax regulations by developing a cutting-edge AI solution for automating the analysis and processing
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(https://engineering.pitt.edu/bioengineering ) is seeking a Research Assistant Professor (Appointment Stream). Incumbent must possess a PhD in Bioengineering, Neuroscience, Neurobiology, Biomedical
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engagement. You will have the opportunity to shape the focus of your research according to your background and interests, with an emphasis either on iPSC-based disease modelling or on computational analysis