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, including abstract geospatial workflows; design AI- and machine-learning-based methods that automatically describe and model geodata sources using textual metadata (NLP) and the geodata itself; contribute
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methods or desire to work on Applied Machine Learning Problems > Constantly questions finance/trading data and stays motivated to seek answers despite most often proving that there is no correlation
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Do you enjoy integrating hardware and software? Join us in developing virtual laboratories and platforms that support innovative teaching and enhance hands-on learning and hybrid education
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mathematics, electronics and computer technology to contribute to the development of Information and Communication Technology (ICT). With ICT present in almost every device and product we use nowadays, we
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University Medical Center Utrecht (UMC Utrecht); Published yesterday | Netherlands | about 2 months ago
for non-invasive cancer diagnosis and monitoring treatment response. This research focuses on developing this technology for clinical MRI machines for brain, breast, and prostate cancer, three
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fte Introduction Do you combine strong commercial instincts with an understanding of how learning and development drives business success? At RSM BV, we’re looking for a Key Account Manager who can turn
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week) and we require that you work on campus at least 2 days per week. On the other days, it is possible to work from home. We ensure you are provided with a notebook computer and accessories. As the
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addition to microbiological research and routine analyses of food and feed, we also conduct food safety risk predictions in the continuously evolving agri-food chain and apply machine learning to food safety challenges. What
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Erasmus MC (University Medical Center Rotterdam); Published today | Netherlands | about 2 months ago
(CARs) or T cell receptors (TCRs). CAR-T cell therapy has elicited profound responses in hematological malignancies, whereas TIL and TCR-T cell treatments have shown responses in solid tumors, such as
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-on monitoring with cutting edge data-driven and physical based models, including the deployment of machine learning algorithms. The project aims to have a tangible impact on the way urban waters are monitored