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Postdoc in assessing carbon sequestration potential of different wetlands as nature-based solutio...
five bioclimatic zones. Your task will be to combine multi-source data — including field observations, environmental measurements, and satellite imagery — with mechanistic models to assess carbon
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October or as soon as possible thereafter. Jobdescription This postdoc position offers a unique opportunity to bridge environmental modelling, behavioral insight, and policy innovation to understand and
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Job Description Are you looking to grow your career in intelligent embedded systems and edge computing? Join the Embedded Systems Engineering (ESE) research section at DTU Compute , where your
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to modify their function in cellular models in tissue culture together with external collaborators. In addition: The lab has a focus on innovation in science and the project has an application oriented focus
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, or landscape modelling Further, we will prefer candidates with some of the following qualifications: Teaching and supervision experience at the BSc and MSc level Interest and preferably experience in developing
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to integrate various structural biology data (NMR, SAXS, FRET, EPR) as well as computational models and simulations to create and interpret conformational ensembles of disordered protein regions, with the goal
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, district heating systems and energy communities Modelling and testing demand response of district heating systems, e.g., peak load reduction and return water temperature reduction Developing and evaluating
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will benefit from Lonza’s expertise and technology within peptide T cell immunogenicity, and the vast expertise within immunoinformatics and machine learning models at DTU to address this challenge
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use your skills to answer fundamental biological questions in health and disease. The successful candidate is expected to leverage their skills in proteomics and computational analysis to interrogate
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hardware accelerators, or quantum information science. Responsibilities and Qualifications Your primary responsibilities will be centered around the fabrication and characterization of TFLN/TFLT PICs