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are considered a plus. Ability to work independently and generate creative solutions within the project framework. Documented experience in publishing scientific results in peer-reviewed journals. Enthusiasm
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and creativity, be open and honest and to conduct research responsibly, be excited about large challenges and enjoy solving them, have an extraordinary drive towards achieving groundbreaking results
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tasks will be: Develop and apply electromagnetic modelling techniques in combination with inverse design to study light-matter interactions in dielectric nanostructured optical surfaces. Evaluate optical
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the project. Your main tasks will be: Develop and apply electromagnetic modelling techniques in combination with inverse design to study light-matter interactions in dielectric nanostructured optical surfaces
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functionalization and a detailed knowledge about interactions between nanoparticles and living organisms? Are you looking for an ideal springboard for a future career as a scientist in either academia or in industry
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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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and degree programmes engage in international collaboration and share the common goal of contributing to the development of knowledge, welfare and culture in interaction with society. Read more at
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Analytics Research Team The Multi-omics Network Analytics research lab (MoNA - https://multiomics-analytics-group.github.io/ ) is an international, dynamic, and creative team dedicated to getting a holistic
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solutions and policy impacts. You will design and implement machine-learning algorithms that interact with your simulation framework for scenario discovery, building surrogate models of simulation outputs
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at the Department of Food Science, Faculty of Science, University of Copenhagen, and located at the Frederiksberg Campus. We offer creative and stimulating working conditions in a dynamic and international research