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machine learning for molecular and material design; quantum computing for bioinformatics; quantum approaches for safe and sustainable molecular design; and benchmarking quantum simulations of materials
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demonstrable experience with programming in Python and implementing statistical or machine learning algorithms. You have experience with software development practices such as testing and version control with
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eager to combine computer vision, biomechanics, and synthetic data generation to build tools that will shape the future of home-based rehabilitation monitoring. You bring: A PhD in Biomechanical
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initiatives, and establish standards to advance machine learning ( OpenML.org ) OpenML is a popular open science platform for sharing interconnected AI artifacts (e.g., datasets, models, and benchmarks) using
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people with limited arm and shoulder function. Your task will be to explore and develop an AI-enhanced Human-Machine Interface (HMI) that enables a more intuitive and adaptive use of the system in home
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environments, spectral sensing in the visible and near-infrared (NIR) range to estimate sugar and starch content, chlorophyll levels, and plant water status, AI-based computer vision systems to monitor crop
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Are you eager to push optical atomic clocks to new levels in a lively, international research group? Do you enjoy creating complex machines that have never existed before? Do you want to explore
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) with computational methods. The candidate will obtain single-molecule multiplexing data and validate machine learning predictions using the high-throughput data. The successful candidate will collaborate
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Engineering or related disciplines, provided you have a strong interest in communication systems and networking. If you have a solid technical background and are excited about future wireless and satellite
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for the analysis and integration of –omics data. The group has a strong track record in (integrative) computational omics analysis, algorithm development, machine learning and scientific data infrastructure