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. Documented research experience in modern deep learning (e.g. generative models, Bayesian deep learning or large pre-trained models) and excellent programming skills in Python and a modern deep learning
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proficiency in oral and written English, creativity, thoroughness, and a structured approach to problem-solving Additional qualifications Experience with one or more of the following areas is meriting: Bayesian
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ability to work independently and in a structured manner, good collaboration skills, good ability to express yourself in spoken and written English. Additional qualifications Experience in one or more of
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simulations, density functional theory (DFT), molecular simulations, or machine-learning potentials. Experience with generative AI, active learning, uncertainty quantification, Bayesian optimization
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, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) aims to recruit and train the
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at high resolution and the network science methods to study the resulting multilayer structure. This project will, for the first time, build a computational framework that maps coexistence routes across all