273 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" research jobs in Denmark
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written and spoken Willingness to engage in interdisciplinary collaboration and fieldwork Advantageous: Knowledge of bat ecology and species identification Experience with machine learning or automated
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. Further information Further information may be obtained from Prof. Ivan Mijakovic: ivmi@biosustain.dtu.dk You can read more about the hiring department at https://www.biosustain.dtu.dk/ If you are
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at scientific conferences. Excellent English skills, both written and oral Who we are You will be part of the Section for Microbiology. To find out more about who we are check the following page: https
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cultural events including music festivals etc. See e.g. the recent recommendation by CNN (https://edition.cnn.com/travel/article/aarhus-denmark-things-to-do/index.html). Aarhus is easily reached through
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at the intersection of AI, RF, and wireless communication. Your main tasks include developing machine-learning methods for wireless interference detection, mitigation, edge intelligence, and applying AI to optimize RF
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and technical-administrative staff and you have a flair for establishing collaborative relationships. Read more about the Department of Food Science at: https://food.au.dk/ The place of work is
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highly desired. Strong communication skills, the ability to collaborate effectively within the team, and proactive working style are essential. The candidate should be motivated, open to learning new
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University (http://bio.au.dk/en) and work in the Section for Microbiology at this department. The section employs 12 permanent scientific staff and ~20 PhD students and postdocs. Research at the section covers
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students. The department is responsible for two educations: Molecular Biology and Molecular Medicine with a yearly uptake of 160 students in total. Please refer to http://mbg.au.dk/ for further information
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. Who we are The project is led by Jesper Asring Hansen, Associate Professor at Aalborg University and principal investigator of POLSAFE (see profile: https://vbn.aau.dk/da/persons/jajh/ )The research