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PhD Candidate in Exposomics, Machine Learning and Artificial Intelligence Faculty: Faculty of Veterinary Medicine Department: Department Population Health Sciences Hours per week: 36 to 40
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sizes and frequencies by: Measuring rock fractures from UAV data using manual and automated mapping approaches (e.g., machine learning, convolutional neural networks). Monitoring physical weathering
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collaborative, diverse team. This is a unique opportunity to contribute to the foundations for tomorrow’s machine learning. Your job In the ERC project FoRECAST, we aim to develop theory (e.g., new probabilistic
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, including abstract geospatial workflows; design AI- and machine-learning-based methods that automatically describe and model geodata sources using textual metadata (NLP) and the geodata itself; contribute
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transformed not only how we read, but also how we learn to read, bringing both new challenges and exciting opportunities. To fully understand these developments, this project explores the processes underlying
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interdisciplinary research team; learn to independently collect, analyse and interpret your data, share your data at national and international conferences, and prepare manuscripts for publication; contribute
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excellent academic record and demonstrate proven enthusiasm for academic research. You are familiar with qualitative research methods (ethnography, in-depth interviewing). Candidates willing to learn
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, supportive, and intellectually lively environment, where we work hard, learn from each other, and genuinely enjoy what we do. More information For more information, please contact Dr. Fatma Başak Aydemir