503 structures "https:" "https:" "https:" "https:" "https:" "https:" "Helmholtz Zentrum Geesthacht" positions in Netherlands
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- Delft University of Technology (TU Delft); Published yesterday
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spans the full implementation research cycle, including: Collection and synthesis of epidemiological, health-system and policy-relevant data. Supporting structured stakeholder consultations and decision
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HAPP: harmonised appraisal tool for grading and individualised feedback that is integrated into the learning management system (LMS) http://happ.rsm.nl/ Opens external Thesis coach finder: application
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, and behavioral intervention using both quantitative and qualitative approaches, including field studies and stakeholder participation. More information can be found here https
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collaboration with industrial and governmental stakeholders, addressing societal concerns related to land subsidence, uplift, and structural safety in the Grijpskerk, Norg, and Schoonebeek regions. The goal
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leader and follower decisions. We are seeking for a motivated and enthusiastic Postdoc (PD) researcher to join the Combinatorial Optimization group (https://www.tue.nl/en/research/research-groups
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transcription-coupled and other nucleotide excision repair–related DNA repair mechanisms (https://lanslab.eu/publications/ ). This project builds on our previous findings that persistent DNA repair intermediates
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. The project is jointly supervised by Dr. Tarikere Niranjan (https://niranjangroup.weebly.com/prof-tarikere-t-niranjan.html ) and Dr. Emir Efendić (https://eefendic.com ) and examines how decision-makers in
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to apply Website https://www.academictransfer.com/en/jobs/358995/phd-candidate-in-health-economi… Requirements Additional Information Website for additional job details https://www.academictransfer.com
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education at UM, and strive to enable this through inclusive policies and innovative projects led by teams of staff and students. We encourage you to apply for this position. Where to apply Website https
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on Graphs: Symmetry Meets Structure (LOGSMS). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing