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for three consecutive periods (2014-2018 and 2018-2022 and 2023-2026). ICN2 comprises 19 Research Groups, 7 Technical Development and Support Units and Facilities, and 2 Research Platforms, covering different
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pollution associated with human activities, assessing the environmental aspects of different technologies and modeling society’s use of materials. IndEcol combines world-class competence in Life Cycle
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analysis. You master programming in for example Python, MATLAB, or a similar platform and you are motivated to further develop your skills in scientific computing and hyperspectral data processing. You have
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methods (e.g., coding in Python/R, working with APIs, scraping data, building or applying models). • Can bridge theoretical insight with concrete technical implementation and empirical analysis. • Is
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bleeding disorder diagnoses can experience remarkably different clinical outcomes. HemoTwin-BD aims to move bleeding disorder diagnostics beyond traditional disease classifications towards precision
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of the following: A solid foundation in programming (particularly Python) and modern machine learning frameworks (e.g., PyTorch, TensorFlow). An interest in AI security, trustworthy ML, or the reliability of ML
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, Tristan-Gough). Topic 3 will be addressed by geochemical and geodynamic modelling. The 3 PhDs will work on all three topics by using different techniques. The analytical work will be performed in the NIGEL
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with Python-based community tooling such as the BrainGlobe Atlas API. Collaborate with cluster-hire colleagues in behavioral neuroscience, circuit imaging and mapping, and ML/AI to translate research
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collaboration with national and international stakeholders, the project aims to establish a validated, data-driven design framework. Key outcomes will include an open-source Python toolkit, measurable
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environmental pollution associated with human activities, assessing the environmental aspects of different technologies and modeling society’s use of materials. IndEcol combines world-class competence in Life