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recently developed in a commercial 65 nm CMOS imaging process by a large international consortium of engineers and scientists for the ALICE ITS3 upgrade and the future experiments, ePIC@EIC and ALICE3@LHC
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candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development for various hydrogen technologies-based energy systems. Responsibilities
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project aims to address the current limitations of traditional frame-based sensors and associated processing pipelines with a new family of algorithmic architectures that mimic more closely the behaviours
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to numerical simulation algorithms? Then apply now to join our team of theoretical researchers in the Quantum Information and Quantum Many-Body Physics research group. Your personal sphere of play: As a
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of original machine-learning based algorithms and models for multi-modal ultrasound guidance that are intuitive for a non-specialist to use while scanning and trustworthy. You will work with clinical domain
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of Classical Philology / Latin Studies Excellent command of Latin and Ancient Greek A specialization in ancient epic or ancient drama is desirable; interest in literary theory, narratology, and reception history
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Responsibilities Develop suitable algorithmic methods for live and real-time analysis of synchronous and asynchronous data. Write research reports and publications. Analyse and interpret the results of own research
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aims to optimize the operations (serving) of AI by developing algorithms that manage compute, network, and storage resources in a carbon-efficient way while supporting long-term benefits
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Experience in devising and developing novel machine learning algorithms Hands on experience with ROS and physical robots Excellent mathematics skills, particularly in areas relevant to robotics and AI
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-disciplinary research environment Desirable criteria 1. Experience in devising and developing novel machine learning algorithms 2. Hands on experience with ROS and physical robots 3. Excellent