61 modeling-and-simulation-post-doc Postdoctoral positions at Technical University of Denmark in Denmark
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on regulatory mechanisms of cell signalling in several cellular models. The team combines omics technologies with bioinformatics, and functional validation of candidates by biochemical, cell biology, and imaging
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causing these variations in A and F stars. Using asteroseismology, we aim to detect and analyze near-core and surface magnetic fields. This involves comparing theoretical models with photometric
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biosolutions. The institute’s tasks are carried out in interdisciplinary collaboration within e.g. nutrition, chemistry, toxicology, microbiology, epidemiology, modelling, and technology. This is achieved
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approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modeling, aimed at uncover the key traits that define successful microbial biofertilizers
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cross-selectivity. Support the implementation, testing and evaluation of the sensor prototype under simulated and real conditions. Active dissemination of the results in scientific articles and
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-driven analysis and modeling. These are interdisciplinary positions that combine environmental engineering, materials science, and sustainability assessment. We are looking for motivated and forward
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(RAG) models – are shaping professional expertise and practice across diverse Danish public sector domains, especially among frontline workers, including caseworkers, service providers and welfare
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not required. Experience in programming, simulation and data analysis. Ideally also in experiment automation. Ability to work independently and as part of a team. Excellent communication skills in
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academic career in a group with a strong publication track record Work in a supportive, international environment just outside Copenhagen If you want to apply your skills in animal models and translational
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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