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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
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-molecule inhibitors in combination with different non-growth and growth areas be exploited in the design of new AS-ALD processes? How do the surfaces and deposited thin-films evolve during typical ALD
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of Physical AI — and they cut across domains that look different on the surface but share the same scientific core: a robot rehearsing a manipulation task in a digital twin, and a biomedical model simulating
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programming (particularly Python) and modern machine learning frameworks (e.g., PyTorch, TensorFlow). An interest in AI security, trustworthy ML, or the reliability of ML systems in safety-critical settings
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and Probabilistic Thinking - You must enjoy learning and implementing new concepts quickly, combining knowledge from different domains to create new ideas, and take a data-driven and probabilistic