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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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mathematical modelling, with a focus on real-world applications. This includes statistics, uncertainty quantification, data analysis, signal processing, (mathematical foundations of) machine learning, and
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processing, (mathematical foundations of) machine learning, and dynamical systems. Your job In this position, you will divide your time roughly equally between research and teaching (approximately 50% each
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-antibodies. You will focus on the identification of these antibodies by using mass spectrometry based de novo sequencing, machine learning and AI-tools to interpret the data. Your job The primary objective
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mass spectrometry based de novo sequencing, machine learning and AI-tools to interpret the data. Your job The primary objective of the project is to further develop mass spectrometry-based techniques
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programming applications (e.g., experimental design, machine learning for science). We do so by bringing together a diverse team of PhD candidates who will focus on three key areas: Probabilistic and
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an additional planning instrument? Are you excited to unlock the enormous potential of generative AI for urban planning? What will you do? In this PhD you will lead the research and prototyping that brings AI
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geospatial workflows on an abstract level, using purpose-driven concepts and conceptual transformations; develop AI and machine learning based technology to automate the description and modeling of data