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the implications for forest ecosystem service supply. The main methodological approach applied will be forest landscape simulation modelling using the model iLand. The work is embedded in the BETA-FOR project (https
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employeeship and offers safe, favourable working conditions? We welcome you to apply for a PhD position at Uppsala University. The Department of Information Technology holds a leading position in both research
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . The research fellow will focus on foundation model-based world model development for embodied intelligence, and
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Job related to staff position within a Research Infrastructure? No Offer Description Call for Postdoctoral Researchers in Artificial Intelligence (AI) – Focus on Large Language Models (LLMs
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Postdoctoral Opportunity in Molecular Biology to Model the Progression of Rheumatoid Arthritis (M/F)
the DigiTREAT project (PEPR Digital Health), which aims to model the progression of rheumatoid arthritis and its evolution in the presence of drug treatment. As part of this project, the postdoctoral researcher
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. Description: This opportunity is closed to applicants who are Senior Fellows (5-years or more past PhD). The accuracy of space geodesy is limited by mis-modeling path delay in the neutral atmosphere. The focus
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alter near-bed hydrodynamics. This PhD aims to improve the understanding of scour processes around a pile under realistic wave-current conditions. The study will combine physical modeling in a wave
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Master’s or PhD degree in relevant areas will be advantageous. Familiarity with the following areas is advantageous: Participation in Kaggle competitions, showcasing practical problem-solving and model
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the recruitment date, and must not already hold a PhD/doctoral degree. How to apply: The job description and essential/desirable criteria for this role can be found here: https://www.kcl.ac.uk/jobs
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mechanisms. The objective of this PhD project is to develop AI-based surrogate models for microstructure-aware macroscopic mechanical behavior by leveraging the large datasets generated within the AMMETIS