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hold a PhD in physics, but other fields within the natural sciences may be considered for applicants with a strong profile on the points listed below. Experience with experiments based on femtosecond
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and Mechanical Engineering (DTU Construct). In this role, you are advancing innovation by integrating material science, advanced processing techniques, and modelling to gain a comprehensive
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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
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hold a PhD in physics, but other fields within the natural sciences may be considered for applicants with a strong profile on the points listed below. Experience with experiments based on femtosecond
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qualifications: Experience with GHG flux measurements (eddy covariance, chambers) or nutrient flux monitoring. Skills in process-based modelling or ecosystem resilience assessment. Teaching and supervision
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using different materials, producing a comprehensive dataset of structures and their optical properties. This dataset will serve as input for AI-based design tools developed by collaborators within
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including supervision of BSc and MSc students associated with the project As a formal qualification, you must hold a PhD degree (or equivalent). In the assessment of the candidates, consideration will be
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degree (PhD) in electronics, robotics, mechatronics, electrical engineering, embedded electronics, or a related subject area. The applicant is expected to have relevant research and teaching experiences
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microbiology Animal infection models Use of pigs as a model organism Immunogenicity assessment (e.g., ELISA, flow cytometry, cell culture-based assays) Cell culture infection assays Applicants with experience in
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to generate new knowledge within biomedical research areas such as infection and inflammation, membranes, neuroscience and personalised medicine. The Department of Biomedicine provides research-based teaching