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Field
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aims to identify biomarkers in the eye and brain that explain vision loss, building on our previously-developed method linking clinical, neural and behavioral data (Allen et al., 2018; Miller et al
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large multi-dimensional datasets using statistical tools such as positive matrix factorization (PMF) and cluster analysis Investigate the influence of different urban emission sectors on atmospheric
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to contribute to tackling one of the big challenges of our time – then you may want to apply to the position in our team, which is expected to start on 01.11.2025. Appointment is conditional on approval by
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. The candidate must hold a PhD in Urban or Rural Development, Civil Engineering or related domain. The candidate is expected to have hands-on experience in field related to urban or rural planning, renewable
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models; 2. Statistical methods, analysis, and inference for large-scale computational simulator applications; 3. Uncertainty representation, quantification and propagation; and 4. Scalable data science
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will primarily involve conducting large-scale data synthesis projects to better understand the drivers of urban metacommunities and biodiversity patterns. In particular, the lab is interested in
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planning and control concepts to organize customization in secondary education. A large groups of schools and other external partners provide the opportunity for interfacing research and implementation
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*Strong publication record (relative to degree timing) *Collaborative spirit in interacting with postdoctoral and PhD researchers on the team *Interest in developing and applying Large Language Models (LLM
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Sheets. Experience with data cleaning, management, and quantitative analysis using R. Experience in computational text analysis, using machine learning and/or large language models (e.g., ChatGPT
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university deep tech startups, carry out independent, high-quality research leveraging this data, and engage with stakeholders in the Danish and international deep tech arena. Responsibilities and