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DTU Tenure Track Researcher on Nanoreactors for Operando Visualizations of Nanoparticle Catalysis...
of statistical methods in quantification of EELS data, in particularly. Prior experience with advancing EELS measurements of captive gas (of nanoliter volumes within MEMS structures) is a big advantage, and so is
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, programming languages, scientific computing, and statistical physics communities. Depending on your background and interests, your project could involve: developing new differential and probabilistic
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quantitative/statistical and bioinformatics skills. You will coordinate collaboration by managing cross-team experiments. You will write and publish your research in leading scientific journals and communicate
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programming skills and an interest in public health. You have the following expertise: MSc degree in (mathematical or computational) biology, (bio)statistics, econometrics or closely related field; modelling
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. Project website: https://www.list.lu/en/environment/project/forfus/ Is your profile described below? Are you our future colleague? Apply now! Education • MSc or equivalent in hydrology or other
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and air concentrations are measured and modelled Where to apply Website https://www.academictransfer.com/en/jobs/357793/phd-candidate-on-impacts-of-nit… Requirements Specific Requirements An MSc degree
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for developing future-proof protein cropping systems. Where to apply Website https://www.academictransfer.com/en/jobs/358117/phd-position-biodiversity-posit… Requirements Specific Requirements You are a highly
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for developing future-proof protein cropping systems. Where to apply Website https://www.academictransfer.com/en/jobs/358120/phd-position-designing-cropping… Requirements Specific Requirements You are a highly
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their decisions and businesses in their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? You will be part of the LIST Materials Research and
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environmental factors such as fluctuating wind speeds and saltwater exposure. Using advanced statistical and machine learning techniques, including Bayesian inference and stochastic modelling, the project will