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Field
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their connection to the group’s activities in their cover letter. Possible research topics include: Collaborative, federated or decentralized learning/Continual learning and knowledge sharing/Optimization
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learning, and porous materials strong analytical and problem-solving skills ability to work independently and collaboratively in an interdisciplinary team excellent communication skills in English
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consortium. The group offers well-equipped laboratories, a highly collaborative international environment and membership of the Cluster of Excellence "Machine Learning: New Perspectives for Science", which is
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to academic feedback. The work will be grounded in psychological theories of learning and motivation. We welcome applicants from psychology, cognitive science, cognitive and affective neuroscience
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position, conditional on final funding agreement, offers a unique opportunity in the field of data-driven Earth system modelling in close collaboration with domain and machine learning experts. The position
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studies using 2D and 3D cell culture models, e.g. human organoids Apply and develop cutting-edge techniques in virology, cell biology, molecular biology Establish and maintain collaborative projects within
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and collaboration skills Fluent in English Please feel free to apply for the position even if you do not have all the required skills and knowledge. We may be able to teach you missing skills during
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approaches Encouragement to pursue own research ideas Opportunity to develop an independent scientific profile Possibility to acquire funding to support future projects REQUIREMENTS: Highly motivated and
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laboratories, a highly collaborative international environment and membership of the Cluster of Excellence "Machine Learning: New Perspectives for Science", which is funded by the DFG and is located
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. The project involves close collaboration with experimentalists who provide the relevant data. Machine learning methods will be applied to link experimental (imaging) data to a mechanistic model. The results