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Field
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those with demonstrated expertise in mine design, ventilation, technical studies, or emerging technologies. Professionals with demonstrated expertise in mining data analytics, mining data management
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demonstration basins across Europe, based on the integration of high-resolution EO data and advanced text-mining techniques to characterize biophysical and hydrological dynamics relevant to water resilience
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, resource-efficient mining. Duties As a PhD student, you are expected to perform both experimental and theoretical work within your research studies as well as communicate your results at national and
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Automated Vehicles in Rural and Remote Regions. Scholarship details Study levels Research and PhD Student type Future students and Current students Study area Data science, Design, Engineering, Health
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related to staff position within a Research Infrastructure? No Offer Description PhD Positions in Data Science The Munich School for Data Science (MUDS) is a joint initiative of Helmholtz Munich
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solutions to major environmental challenges. Experience with advanced cloning systems, CRISPR tools, metagenomic mining and the use of different biofilm imaging platforms is highly desirable. There
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, deep learning and data-mining methods to address complex research questions. They will lead the analysis of large-scale, heterogeneous datasets, including sequencing, sensor, biological and medical
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mining. Duties As a PhD student, you are expected to perform both experimental and theoretical work within your research studies as well as communicate your results at national and international
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science; natural language processing; information retrieval; data mining. Previous experience as an instructor at the university-level is required. Related work experience will be taken into consideration
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Inria, the French national research institute for the digital sciences | Villeneuve, Queensland | Australia | 24 days ago
to self-adaptive systems. We focus particularly on two properties: self-healing and self-optimization. With self-healing, we aim to study and adapt data mining and machine learning solutions to the