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machine learning methods in the context of biological systems Experience with programming (e.g., Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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variables related to the weather conditions, road surface micro- and macro-texture, tire properties, driving speed, and behaviours of road users. This project aims at studying different data sources such as
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mission is directly tied to the humanity, dignity and inherent value of each employee, patient, community member and supporter. Our commitment to learning across our differences and similarities make us
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); Experience of statistical or other programming languages to manipulate large-scale datasets – e.g. Python, R; Strong quantitative skills and analytical reasoning applied to observational data; A track record
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Randomization, co-localisation); Experience of statistical or other programming languages to manipulate large-scale datasets – e.g. Python, R; Strong quantitative skills and analytical reasoning applied
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duties will be the following: Manipulate and culture different types of primary and stem cells (including induced pluripotent stem cells) and tissue constructs, particularly at the genetic level, and
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) assess future changes in these patterns under different global warming scenarios. Requirements: The successful applicant should hold a MSc or PhD degree in physics, mathematics/statistics, climate science
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resilience and its change over time in the past (based on Earth observation data), present and future (based on Earth system model simulations for different future scenarios, e.g. using the CMIP6 ensemble and
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development. Experience with implementing statistical learning or machine learning (e.g. Bayesian inference, deep-learning). Programming skills in Python and experience with frameworks like PyTorch, Keras, Pyro
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Postdoc in assessing carbon sequestration potential of different wetlands as nature-based solutio...
The Department of Agroecology at Aarhus University, Denmark, is offering a postdoctoral position in assessing carbon sequestration potential of wetlands as nature-based solutions under different