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highly interdisciplinary research environment combining experimental neuroscience, biophysical modeling, and clinical data analysis, embedded in a strong national and international network. Your salary and
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research network called NiteLiDAR. We want to use the results of this research, together with our partners, to create innovative demonstrators for the next generation of LiDARs. In the second step you will
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gameplay analysis, your work supports better digital health interventions, fairer game design, and evidence-informed European policy on deceptive and harmful digital practices. Where to apply Website https
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estimation using multi-track Sentinel-1 (C-band) and NISAR (L-band) data. Implement and extend dynamic InSAR processing workflows for near-real-time analysis, including quality control and anomaly detection
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biotypes; within-target personalized coil positioning, using MRI-guided neuronavigation and network-based metrics to optimize stimulation for each individual; n-of-1 trial design in clinical care, embedding
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). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing provably powerful learning models for graphs will
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infrastructures, healthy urban living, urban inequalities and diversities, transnational mobilities, economic resilience and networks and flows in and between urban regions. For our NWO Cooperation Indonesia
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related field, and a strong interest in biomedical applications. Experience in machine learning, statistics, or high-dimensional biological data analysis is advantageous. Ideal candidates are curious
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academic activities with creativity and rigour, and demonstrate a proactive approach to empirical research, analysis, and writing. Your work combines a strong theoretical grounding with applied knowledge
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exploitation of PRIDE (Planetary Radio Interferometry and Doppler Experiment) observations by developing and applying open, reproducible analysis pipelines for deep-space mission tracking. You will be embedded