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empathic person with a PhD degree in mechatronics engineering, MEMS, neurotechnologies, applied physics, nanotechnology, neural interfaces, biomedical engineering or similar. Advanced skills in electronics
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from water samples compared to tissue samples for early detection of disease. Another is to perform “what if” scenario modelling to compare suitability for different sampling protocols in farms in non
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the department’s competencies in advanced modelling and control of buildings' energy systems, e.g., heating, cooling, and ventilation systems using IoT technologies. You will collaborate closely with academic and
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describe concrete examples of your own relevant previous work involving these topics). Experience with modelling is an asset. As a formal qualification, you must hold a PhD degree (or equivalent). We offer
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Do you have experience with modelling structures subjected to dynamic loading? Are you interested in data-driven methods for modelling applied loading? Are you eager to share your knowledge within
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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, you are expected to determine the molecular super-structure of TZ. You will monitor the gating mechanism of TZ in cellular models such as RPE1 or cultured dopaminergic neurons by immunofluorescence
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project supported by the Challenge Programme of the Novo Nordisk Foundation: “Mathematical Modelling for Microbial Community Induced Metabolic Diseases”, led by Prof. Daniel Merkle. The expected starting
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necessary. As a formal qualification, you must hold a PhD degree (or equivalent). We offer DTU is a leading technical university globally recognized for the excellence of its research, education, innovation
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models to quantify phenological responses. Collaborate with internal and external partners, including leading researchers in phenology and population biology. Mentor master's students participating in