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Field
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weather forecasting to cardiovascular medicine. Computational tools for simulating such processes - both traditional based e.g. on computational fluid dynamics and more recent based on AI/machine learning
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. Computational tools for simulating such processes - both traditional based e.g. on computational fluid dynamics and more recent based on AI/machine learning - constitute fundamental scientific domains that act as
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processes with more realism in the project. The post will involve global modeling with this new climate model at Lund to investigate mechanisms for the effect from ice nucleating aerosols on clouds and
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processing and writing. You will also take courses at the doctoral level, participate in international conferences, and have the opportunity to develop your networks across various academic disciplines and
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collaboration with farmers who are already testing these systems. As a PhD student within this project, your work will include field station and on-farm experiments, as well as data processing and writing. You
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strong interest for microbial soil processes and an ability to conduct field work in remote places. A driving license valid in Sweden (required for accessing the field sites) Merits: Merits
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) scientific studies Experience with relevant field data collection methods (e.g. chamber- or eddy covariance-based C flux measurements, biodiversity sampling methods) Computer programming skills (e.g. Matlab, R
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unhealthy adipose tissue expansion and how sex differences influence these processes. The doctoral student project and the duties of the doctoral student This doctoral project will focus on characterization
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under the three categories: 1. Method validation 2. Fundamental ecological processes & forestry impacts 3. Conservation & monitoring framework Qualifications: - Master’s degree in ecology, biology
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its dependency on the pre-fire forest structure and management practices in Fennoscandian boreal forests. Work includes e.g. developing methods to assess burn severity and fuel structure, processing