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, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted
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Job Description The Center for Polariton-driven Light–Matter Interactions (POLIMA) at the Mads Clausen Institute, University of Southern Denmark (SDU) is seeking a highly motivated postdoctoral
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product detection and the GC calibrated. While Spectro Inlets will develop the elevated temperature and pressure EC-MS, this is a collaborative project, thus there will likely be interactions and lab visits
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Science including quantitative and qualitative consumer research methodologies, and experience in designing consumer studies in and out-side Denmark. Solid experience in statistical analysis are preferred
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. Experience with faba bean cultivation and inoculation, legume-rhizobium interactions and plant and rhizobium molecular genetics and genomics is an advantage. Applicants should hold a PhD in molecular biology
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system, and the research will interact closely with the quantum computing team. We expect you to be intrigued by the potential of using synthetic dimensions and quantum optics to explore the physical world
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intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and
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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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. In terms of research The position includes research within the project Best for Us (in Danish, Bedst for Os) https://bedstforos.dk/ . Best for Us is a large research project aimed at investigating
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manipulating photons at the nanoscale, with strong expertise in design, modelling, and nanofabrication of III–V optoelectronic and nanophotonic structures. Hy-Q is a center of excellence funded by the Danish