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Python, R or similar, excellent communication and organisational skills, and the ability to work both independently and collaboratively. Experience with large and complex AI problems, novel AI
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Familiarity with Python and Callista data is desirable About Monash University At Monash , work feels different. There’s a sense of belonging, from contributing to something ground breaking – a place where
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different dyadic motor coordination tasks. A range of neurophysiological measures (EEG, ECG and fNIRS) as well as behavioural measures will be recorded simultaneously from both partners. Machine-learning
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If Limited Term (End Date of Assignment, Project, or Grant) Position Type Staff Job Family Information Technology # Hours Per Week 37.5 Position Overview Be The Difference Begins with Great People. Are you
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++, Python, ROS/ROS2) A strong track record of writing and maintaining technical program documentation and operational procedures. Expertise and experience in using AI approaches for automating navigation and
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role focuses on improving and implementing procedures for the automated processing and visualization of this data using Python. Be part of change Raw data manipulation: Handling and transforming raw data
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than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries. Software Developer, circular-construction AI (REON / SXL) Mission The Structural Xploration Lab
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. The candidate will lead the C++ / Unreal Engine software engineering efforts, ensuring sub-millisecond data synchronization between simulation frameworks and external Python-based AI models hosted at partner
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include: - Extension to radio and optical diagnostics to test different interaction scenarios - Extension to low mass binary interactions at optical wavelengths - Development of empirically motivated models
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Divergence (MIND) approach for estimating structural similarity networks, which enables robust structural brain networks to be derived from T1-weighted images alone and has already been shown to be sensitive