244 programming-"the"-"DAAD"-"UCL"-"FEMTO-ST"-"Prof"-"IMPRS-ML"-"https:" "DIFFER" positions in Netherlands
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- Wageningen University and Research Center
- Delft University of Technology (TU Delft); Delft
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(Enabling biodiversity-positive transformation of energy planning towards climate neutrality), funded through the Biodiversa+ programme, brings together leading universities and research institutes from
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limitations that cannot be overcome with bigger models and larger datasets. A critical issue is the embedding of hierarchies, for which a different geometry is better suited, namely hyperbolic geometry. Seminal
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globalization, modernization, individualization, and multiculturalism—and their impact on cohesion, inequality, and identity. It offers Bachelor's, Master's, and Pre-master Sociology programs (in Dutch) and
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Teaser Text The AI in Education (AIED) programme manager at Universiteit Leiden is seeking a motivated Student Assistant with a background in Educational Sciences to support our project managers and
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for organizing and maintaining our proteomics workflow, using high-end equipment such as a liquid-handling station and mass spectrometers. You will prepare samples for different research lines in close
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guides the team, helps you find your way in our organization, and facilitates your personal and professional development. You will contribute to various research projects within different groups
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techniques, you will contribute to the development of (new) methods for processing, analysing, and preserving different types of samples. You will work on a range of projects, including the cryopreservation
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participatory workshops where citizens and decision-makers experience and evaluate different urban scenarios in VR. Collect and process data from these sessions, combining objective indicators (e.g., space use
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pedestrian-micromobility mode interaction. Identify key indicators of stress and discomfort for different types of vulnerable road users. Collaborate closely with other project partners across different work
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record in machine-learning methods for computational physics. Proven programming skills in (preferably) Fortran or Julia, or C/C++ and Python. Where applicable, a link to your open source repositories is