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preference in the hiring process. The University of Tübingen is committed to equal opportunities and diversity. It therefore takes individual situations into account and asks for relevant information
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be expected to teach advanced courses in Artificial Intelligence—particularly in machine learning, statistical learning, natural language processing (NLP), symbolic AI, computer vision, and related
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provided throughout the recruitment process. Enjoy an outstanding career environment We offer a uniquely rewarding workplace. The size, breadth and quality of our education and research programs - including
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inequalities shape carers’ lives using qualitative and creative methods (e.g. Theatre of the Oppressed, or others). 2) To support the co-production process across our team and partner organisations (e.g. Black
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. Candidates should have excellent programming, communication, and organizational skills. Ideally, candidates should have previous knowledge of image processing, statistics, and machine learning/AI, and
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and their by-products. o Monitor and control the migration of radionuclides and heavy metals throughout industrial processes. 2. Optimization of Industrial Processes: o Utilize nuclear
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Your profile: • University degree (MSc or PhD) in any of physics, engineering, medicine or biology. • Experience in optics and signal processing that allows a quick adaption to the technological needs
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Applications are invited for two Research Assistant / Research Associate posts on the project EQUATE - a project that investigates how Natural Language Processing (NLP) could be made globally more
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teaching and therefore urges qualified women academics to apply for these positions. Equally qualified applicants with disabilities will be given preference in the hiring process. The University of Tübingen
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such as the NEPS. Potential research areas include (but are not limited to): Item response modeling of achievement tests Analysis of process data (e.g., response times) to enhance competence measurements