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Field
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Requirements A PhD in computer science, artificial intelligence, human–computer interaction, computational social science, digital humanities, cognitive science, or a related field; Experience with
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, data analysis and programming, preferably in Python you have knowledge of climate adaptation, infrastructure resilience, decision making under (deep) uncertainty or cost benefit analysis you have
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conditions, drawing on survey data, earth observation outputs, and qualitative inquiry from all consortium partners. Mentorship and capacity strengthening Contribute to the supervision and mentoring of PhD and
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analytical and problem-solving skills. Experience with data analysis, numerical modelling or programming, for example in MATLAB, Python or similar tools. Good written and verbal communication skills in English
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remote sensing data. What you will do Changing fire dynamics will be studied using a Dynamic Global Vegetation Model (DGVM), allowing us to quantify different mechanistic processes. Using high-resolution
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the VITAL consortium and contribute to patient-specific or cohort-level virtual human twin simulations. You will also contribute to patient-specific model calibration workflows, including sensitivity analysis
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synchronized to each patient's evolving gait dynamics as they recover. You will: Retrain an IMU-based gait-detection algorithm using stroke-patient data Run patient panels with stroke survivors, with a PhD
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subsurface. Job description We are looking for a candidate who will investigate the regional geology of the Saharan Platform. This will build on top of the ~100 publications and PhD theses from the North
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-patient data Run patient panels with stroke survivors, with a PhD candidate, to assess fit, comfort, and usability Tune and clinically assess FES stimulation with physical therapists at Sint Maartenskliniek
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from clinical specimens; Develop, optimize, and apply DIA- and PRM-based proteomics methods; Perform quantitative data analysis, normalization, quality control, and statistical interpretation