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) signal processing, machine/deep-learning and computational linguistics. The team mobilizes them to produce methodologically sound research in response to some of the challenges posed by the nature and
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questions and data of CREATE. The successful candidate will conduct advanced methodological and psychometric research. Potential topics include (a) AI, machine learning, and large language models
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student in areas related to Computer Science. Basic experience in health data analysis. Python programming. Knowledge of machine models and deep learning. Intermediate English level. Specific Requirements
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work on the molecular genetics of age-related hearing loss (https://www.grilletlab.com/). The Grillet lab has generated a mouse model carrying a polymorphism identified in Genome Wide Association Studies
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Systems at The Technical Faculty of IT and Design invites applications for PhD stipends or integrated stipends in the field of Machine Learning for Intelligent Hearing Assistance in Complex Acoustic
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in the project proposal for Profile 7, in particular: Task3: Multimodal Data Analysis and Machine Learning; Task4: Coating Optimization and task: Dissemination. The work will focus on the study and
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research. You will strengthen the data science and machine learning activities of IAS-9 by developing core AI methods with applications to electron microscopy and materials discovery. You will work in a team
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, Effects, and Criticality Analysis (FMECA), functional FMECA, advanced sensing techniques, sensor and operational data fusion, data analytics, and machine learning algorithms for condition monitoring, fault
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: MSc degree completed. Additional optional skills and qualifications: Previous research experience, particularly in the fields of Internet of Things security and machine learning models applied
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) are required - Experience in working with Earth system model simulations is required - Experience in machine learning is required - Willingness to travel for work (project meetings, workshops, and research