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Two year postdoc position at Aarhus University for single molecule FRET based investigations of l...
in the target proteins. The postdoc will collect single molecule FRET data and by integration with existing atomic models establish trajectories for key conformational changes in the investigated
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with experience in one of the following directions: Analysis of meta-omics data sets, microbial physiology and cultivation, enzyme biochemistry or activity-based microscopy techniques (e.g. BONCAT
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at the intersection of digital building technologies, data science, and energy systems. By joining our forward-thinking section Digital Building Technologies at DTU Construct, you will gain hands-on experience in
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that also act as green energy producers driving the societal transition towards net zero. In this position, you will build on your expertise in IoT and low-power computer and communication systems to research
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. Quantifying circular economy strategies for wind turbine rotor blades, including reuse, recycling, and feedback loops. Assessing the climate mitigation potential of circular construction materials through data
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research environment focusing on integrating multi-source data and developing novel algorithms to address the challenges posed by global environmental change. You will focus on integrating experiments, field
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design to testing, programming neural interfaces, neural data analysis. We offer DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and
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process modelling, experimental data, model parameters and modelling approaches in order to optimize design, analysis and operation of complete capture processes. The goal of the project is to develop
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collaboration between research groups at several departments at Aarhus University. For further information, please contact Professor Kurt Gothelf +45 60 20 27 25 kvg@chem.au.dk Application procedure Shortlisting
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within our portfolio of hypothesis-generating screening studies, a methodological portfolio where we identify signals of interest from real-world register data to guide the conduct of tailored studies. We