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wide range of resources and is mostly not publicly available. While sharing proprietary data to train machine learning models is not an option, training models on multiple distributed data sources
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”. Are you excited about the opportunities that data science in nutrition—especially the role of targeted metabolic modelling, machine learning and AI offer in developing effective personalized nutrition
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background in data sciences we ask: Insights in the most suitable data science techniques (e.g., machine learning, cluster analysis) to answer specific research questions based on available data as a basis for
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Essentials PhD (completed or near completion) in Computer Science, Computer Vision, NLP, Machine Learning, Computer Graphics/Animation, HCI, or a related field. Strong background in deep generative
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subpopulations, as well as (plastic) cancer cell states that contribute to tumor progression, metastasis and therapy resistance. The candidate will lead several projects applying machine learning to (single-cell
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electron ground states. Another promising route towards physical implementations of energy-based machine learning and neuromorphic hardware is to utilise material platforms that exhibit multiwell behaviour
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Vacancies Postdoc position on deep learning based medical imaging for medical robot Key takeaways In this role, you will help develop and implement cutting-edge AI solutions for real-time, image
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developers, electrical and mechanical engineers. Experience and strong understanding of machine learning algorithms, mathematical modelling, and applications of AI. Proficiency in Python, leading ML frameworks
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, machine learning, automatic control and physical interaction of intelligent machines with humans. We combine fundamental research with work on physical demonstrators in areas such as self-driving vehicles
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within a cross-functional team, including software developers, electrical and mechanical engineers. Experience and strong understanding of machine learning algorithms, mathematical modelling, and