41 network-coding-"Chung-Ang-University"-"Chung-Ang-University" positions at Aarhus University in Denmark
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topics: Predictive Coding of Music, led by Peter Vuust (PI, Director) Multimodal Theme, led by Boris Kleber Music Interactions, led by Peter Keller Meaning of Music, led by Elvira Brattico (PI) and Morten
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of understanding their regulation by phosphorylation. You will be in charge of writing and testing code, developing, deploying and maintaining software. Your work will benefit from the experimental data generated by
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working relationships, networking and social activities characterized by professionalism and equality. Aarhus University offers a good work-life balance. English is spoken widely, even if Danish is the main
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and a broad academic network, you contribute to the academic development at Aarhus University and to the university’s profile both nationally and internationally. Your main tasks will consist
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lively, open and critical discussion within and across different fields of research a work environment with close working relationships, networking and social activities a workplace characterised by
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industrial collaborators A work environment with close working relationships, networking and social activities Opportunities for career development Place of work and area of employment The place of work is
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collaborators a research climate encouraging lively, open and critical discussion within and across different fields of research a work environment with close working relationships, networking and social
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maintains a high academic and didactic standard. You possess professional collaborative skills and a broad academic network which you are able to bring into play in your contribution to the academic
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training a mentoring programme support to develop scientific networks and to secure interdisciplinary research at the highest level As part of the Aarhus University Tenure Track Programme, the University
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computational models to map co-expression networks and predict systemic disease transitions. Characterise intestinal microbiome changes and their correlation with inflammatory diseases. Computational modelling