597 algorithm-development-"Multiple"-"Simons-Foundation"-"Embry-Riddle-Aeronautical-University"-"Prof" positions in Netherlands
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Postdoc: Hybrid Geospatial Modelling and Scenario Development of Biomass Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 32 to 40 Application deadline
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, or ESAC, Madrid, Spain, or ECSAT, Harwell, United Kingdom. Description ESA Workplace Development Lead, Development and Coordination Office, Real Estate and Facilities Management Department The European
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Vacancies Academic staff Support staff UT Student Jobs UT as employer UT as employer Employment conditions Career and development Pre and onboarding Tenure Track PhD EngD Working as a UT student
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This is a non-renewable post for a limited duration of four years. Location ESTEC, Noordwijk, Netherlands Description Real Estate and Facilities Management Development Lead, Head of the REFM
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(KTO) plays a central role in translating academic excellence into societal and commercial value. We are looking for a Business & Impact Developer to strengthen our team and help drive the next phase of
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Wageningen University & Research offers excellent terms of employment . A few highlights from our Collective Labour Agreement include: sabbatical leave, study leave, and partially paid parental leave; working hours that can be discussed and arranged so that they allow for the best possible...
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genomic and biochemical diversity and thereby contribute to sustainable food and agriculture. As a group, we contribute to multiple BSc and MSc programmes. We educate new generations of biologists
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focuses on how Dutch and English academic literacy develop within Dutch and English tracks, and how curriculum characteristics may be conducive to this. This involves the analysis of a large sample of
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higher education. Your specific subproject focuses on how Dutch and English academic literacy develop within Dutch and English tracks, and how curriculum characteristics may be conducive
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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