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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
self-assemble from a number of interacting single-stranded DNA molecules. An accurate prediction of DNA structures still remains difficult, which significantly slows down the development of new desirable
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workshops, career development, and networking Join a dynamic institute hosting over ten atmospheric chemistry research groups, offering rich opportunities for collaboration and learning Extensive
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hydrogen release by means of pressure control Carrying out parameter studies Comparison of different catalyst materials Determination of the pressure dependence of the dynamic hydrogen release Development
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of the possible influence of storage-related factors on the LOHC purity Method development and application of suitable analytics (e.g. GC(-MS), NMR, etc.) for the qualitative and quantitative determination of by
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occur, and how can the overloading of individual regions be counteracted? Your contribution to scientific analysis: Further develop existing energy system models in Python to accurately map and analyze
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or diploma in physics, biophysics, applied mathematics, chemistry, or a relevant engineering discipline Strong motivation to study motility of microswimmers and develop computational models Good programming
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Participation in the development of the institute Your Profile: Sucessfully completed scientific university degree (Master) in the fields of technical chemistry, physical chemistry or a comparable discipline
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support the development of a European energy system model by benchmarking future technologies and optimizing their representation within the FINE optimization modelling framework ( https://github.com/FZJ
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the manufacturing and characterization of material samples. As such, the position offers the opportunity to be involved in fruitful national collaborations. In this exciting job you can expect: to develop automated
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Your Job: Maintain, and update quantitative methods for assessing economic impacts of the energy transition at the national and regional levels Develop dynamic and multisectoral economic models