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Field
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. Additionally, doctoral candidates will take basic courses consisting of two main sections each: E-learning courses covering the essentials Cognition academies (classroom weeks) in which all doctoral candidates
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machine learning to improve outcome prediction and patient stratification. deepen our understanding of the etiology, clustering, and diagnostics of cardiovascular diseases in critically ill patients
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an extended period of time. The research classes are based upon the cooperative work of the group and the principle of peer learning. In addition, both faculties offer numerous colloquia that cover key areas
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that he/she can check approve your file . You will have to upload some documents Proof of enrolment as a PhD student at your home University A signed Learning Agreement. Please chose the correct template
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performing data analysis of B cell receptor repertoire data using programming languages (mostly R) Successful candidates can think independently, are eager to acquire necessary new skills, and are excellent
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Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms for the identification of antibiotics-associated proteins and antimicrobial
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, Reasoning and Validation (Serval) research group and work on a research project related to the application of machine learning for official statistics. The subject of the thesis will be “Exploring Large
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novel materials, tools, or artistic creations, humans instinctively explore the unknown in order to acquire information about it, to make sense of it, to act on it, and to appreciate what is in front of
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It is widely accepted that synaptic plasticity constitutes the cellular correlate of learning. Yet, synaptic plasticity alone is insufficient to fully account for learning. Other mechanisms, such as
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behaviour. This will include developing and using state-of-the-art image recognition algorithms to create digital twin models as well as statistical and machine learning methods for analysing large-scale