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Pervasive Systems Research Group at EEMCS Faculty. This PhD position is part of the MULTIPLIER project, a large cross-disciplinary initiative addressing one of the key challenges of the Dutch construction
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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with cell culture, 3D models and in vitro assays. Experience in phototherapy, programming and large data analysis is a plus. Excellent communication skills and fluency in English (written and oral). Our
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the top 10 large employers in the US in 2024, ahead of Google, Microsoft and Apple: https://www.forbes.com/lists/best-large-employers/?sh=70605b987b66 . Top Employer for Women: St. Jude is also among
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sciences increases with new mobile and stationary sensors and observation platforms becoming available, the need for processing these large data streams also increases. Such datasets provide exciting new
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duration of the PhD research. Please see the RePIM project website (https://repimnetwork.eu/recruitment ) for further information. Qualification requirements PhD stipends are allocated to individuals who
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-phd-positions/ . Requirements Top-ranked Master's degree in robotics, computer vision, system control, machine learning, mathematics, or a related field (background in any of the following); Being
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, Oslo. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/291053/phd-research-fellow-in-mathematics Where to apply Website https://www.jobbnorge.no/en/available-jobs/job
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CeMM - Research Center for Molecular Medicine of the Austrian Academy of Sciences | Austria | 13 days ago
to develop your innovation and entrepreneurship skills at the cutting-edge of AI/ML and biomedical research? If yes, apply now of our 15-20 fully funded PhD positions here: https://apply.cemm.at/ Supported by
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to the production and exploitation of large simulation ensembles for the assimilation of paleoclimate data over long climate time scales. · Participate in the scientific exploitation of the simulations produced and