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department under the Faculty of Science & Technology at Aarhus University. Our work spans fields from physics, chemistry, microbiology, molecular biol-ogy, and mathematical modeling to social science
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for teaching and research for the tenure track period CV including employment history, list of publications, H-index and ORCID (see http://orcid.org/ ) Teaching portfolio including documentation of teaching
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general. And more recently, the proposal of Large Language Models opened a wider range of opportunities to explore its use for Software Engineering (LLM4SE). This is the main goal of this research, i.e
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such as Google Earth Engine statistical modelling, machine learning, cloud/high-performance computing retrieving ecologically relevant environmental data from national to global databases research and/or
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populations. Apply Artificial Intelligence (AI) methods including deep learning (DL) models and supervised and unsupervised machine learning (ML) methods for integration and for Genome-2-Phenome (G2P) and risk
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ranges from physics, chemistry, microbiology and mathematical modelling to social science, geography, economics and policy analysis. Both basic and applied research is conducted related to some of the
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Aarhus University. Our work spans fields from physics, chemistry, microbiology, molecular biology, and mathematical modeling to social science, geography, economics, and policy analysis. Both basic and
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in e.g. programming, algorithms and data structures, software systems architecture, use of AI, data acquisition and fullstack software-development. Following the Problem-Based Learning (PBL) model, you
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sensory testing (QST) as well as research based on animal models (e.g. rodents and pigs). CNAP is a dynamic and international research environment: approximately 60% of our staff is international, with a
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applicant is qualified and, if so, for which of the two models. The assessed applicants will have the opportunity to comment on their assessment. You can read about the recruitment process at https