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). Human and environmental exposure modeling (e.g., ConsExpo, Chesar, Vermeer). Proficiency in navigating ECHA databases, and use of chemical safety data (REACH dossiers, hazard classification, exposure
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, protocols, and data standards across collaborating institutions and scales. This collaboration will support the generation of coherent, high-quality datasets and enable the development of predictive models
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on electrochemistry, atomic scale and multi-physics modelling, autonomous materials discovery, materials processing, and structural analyses. We also focus on educating engineering students at all levels, ranging from
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collaboration within e.g. nutrition, chemistry, toxicology, microbiology, epidemiology, modelling, and technology. This is achieved through a strong academic environment of international top class 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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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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. The technologies include fuel cells, electrolysis, power-to-x, batteries, and carbon capture. The research is based on strong competences on electrochemistry, atomic scale and multi-physics modelling, autonomous
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characterization of photonic devices. Desired qualifications: Theoretical understanding of photonic integrated circuits. Experience with numerical modeling. Experience with Python programming. Additionally, we
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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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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