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Field
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. Knowledge in project field PhD student in the economic sciences field, enrolled in a state university from Romania. Being enrolled in a PhD program in the cybernetics and statistics field could be
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, Psychology or a related field excellent knowledge in AI and at least one of these three key areas: quantitative user studies, statistical modelling of human experimental data or human augmentation very good in
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | about 1 month ago
for highly-motivated and qualified candidates to work with an international team on developing cutting-edge novel demographic, statistical and computational methods in estimating, modelling and forecasting
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CO2e annual flux or kt N annual loss to water). These quantitative metrics will be supplemented by expert screening of spatially explicit scenarios in terms of biodiversity and resilience to future
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for listening and reading. Experience in working with human participants, strong technical skills, and experience with data and statistical analysis. Experience in neurostimulation (e.g. transcranial magnetic
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in experiment programming and statistical analyses and excellent written and oral communication skills in English. DCs must comply with the Marie Curie Actions mobility rule: the researcher must not
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on this work by using molecular methods to unravel the forces that modulate mutagenesis across the genome of mutagen-exposed cancer cells. You’ll be introduced to advanced statistical and computational methods
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subject relevant to the proposed PhD project (such as mathematics or statistics) is our standard entry, however we place value on prior experience, enthusiasm for research, and the ability to think and work
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principles that regulate host-pathogen interactions and feedback, using a combination of quantitative imaging, microfluidics, statistical analysis and machine learning tools. A specific focus will be put
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tunnel testing and statistical modelling using extreme value theory, the project will yield predictive frameworks for structural risk under rare yet damaging wind conditions. The results will support