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permafrost soils in the LPJmL Dynamic Global Vegetation Model in the joint project with our project partners you will cooperate with UZH field experts on arctic vegetation to embed and simulate tundra-specific
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an interdisciplinary team, who is eager to both gain and share insight while being focused on publishing papers in leading international journals. Knowledge of the Norwegian language is not required. However, a good
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placement would provide the candidate with great opportunities for engaging with industrial experts through real-life problems, presenting to industrial audiences in annual Dyson Institute conference week
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working. You will be supported by expert supervision and an exceptional research environment. Abertay offer an extensive training and professional development program to enhance research excellence, impact
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Knowledge on forest ecosystem service provisioning Good quantitative skills, specific interest in simulation modelling Good communication skills Ability to work in an interdisciplinary team Your tasks You
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/Electromagnetics theory, design and simulations Machinelearning mathematics and algorithms Numerical methods Programming skills (Python, MATLAB, or similar) Strong analytical and problem-solving skills. Good written
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neuroimaging data Proven record of ability to conduct high quality research in relevant health related subject Previous coding experience (e.g. python, bash, matlab) Good administrative skills, and the ability
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symptoms. A successful candidate will work with experts in chronic pain at the MMU Institute of Sport and collaborate with leading researchers across the globe. The results of this project will underpin
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microscopy, microfluidics or instrumentation will be a significant asset. Good interpersonal skills, scientific rigor and curiosity are essential. LanguagesENGLISHLevelExcellent LanguagesFRENCHLevelBasic
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, physics or a similar area - very good programming skills in Python - good prior experience with neural networks using common Python-ML libraries such as PyTorch - background knowledge in computational