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Field
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Intelligence (AI) and Machine Learning (ML) capabilities into distributed cloud-edge infrastructures to enable autonomous and efficient network/service management. The PhD candidate will investigate innovative
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data set (e.g. neutron irradiations, that take years/decades to generate). Digilab brings AI/ML (artificial intelligence / machine learning) approaches for data engineering and automation to utilise
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; Distributed multi-agent sensing and cooperative positioning algorithms; Machine learning and data-driven methods for ambient awareness. Working Environment: The PhD will be conducted at the University
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different environments influence behaviour and wellbeing. Advanced analytics, including AI and machine learning, will be used to interpret behavioural and emotional data, enabling real-time insights
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Optimization (DPO) and reinforcement learning from human feedback, building preference datasets together with clinicians - Build and run a Red Team process with physicians, computer scientists, and patient
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intelligence, data analytics, uncertainty analysis, probabilistic modelling, or statistical learning you have experience working on relevant research or project activities involving machine learning or data
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in machine learning or deep learning (experience with deep learning frameworks such PyTorch and TensorFlow is a plus). You have solid programming skills in Python. You have programming experience in C
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for machine learning models to optimise membrane properties, structure, and fabrication. The fellow will play a key role in the experimental part of the project, including: Preparation and characterisation
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Degree PhD Learning Sciences (alternatively Dr phil, Dr rer nat, Dr med; not recommended for international students) Course location München Teaching language English Languages Courses are held
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About us VIB.AI, the VIB Center for AI & Computational Biology, is a research center dedicated to integrating machine learning with deep biological insight to understand complex biological systems