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empirical research, particularly experiments, and is comfortable with advanced statistical analyses (experience with R is recommended) possesses excellent academic writing skills in English is sociable, open
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, P&R, timing closure). Knowledge of low-power digital design techniques (e.g., clock/power gating, DVFS). A strong curiosity about the challenges of analog/mixed-signal circuits (ADCs and PAs) and a
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analysis (e.g., Matlab, Python, R) is a plus. Previous experience with EEG and fMRI data analysis is an advantage. Your Team You will join the Brain Stimulation & Cognition Lab at the Faculty of Psychology
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to learn) as you will interact with patients. You have experience with programming and data analysis (e.g., Matlab, Python, R) is a plus. Previous experience with EEG and fMRI data analysis is an advantage
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software (preferably R. MATLAB, Python) Strong interest in cardiovascular physiology, hemodynamic monitoring, and imaging (ECG, CT, echocardiography). Affinity with critical care and working with vulnerable
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Wetsus - European centre of excellence for sustainable water technology | Netherlands | about 2 months ago
data, GIS, and environmental modeling. Familiarity with programming languages such as Python, Julia, R, C++, or MATLAB is considered a strong asset. Experience with fieldwork or working with soil
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quantitative skills (analyses of long-term data, modelling and statistical analyses, particularly quantitative genetics, ideally in the R environment). Is proficient in English and meets the university’s
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models. Experience (or strong willingness to learn) in programming and data analysis (e.g. Python, MATLAB, R, Fortran, or similar). Curiosity and motivation to work on fire emissions, air quality, and
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statistical analyses in R. You possess excellent written and oral communication skills in English. You have previous experience with participating in research projects (e.g. data collection, statistical
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systems. Proven programming skills in Python, R, or a comparable language. Interest in developing methodologies to assess localized climate hazards, exposure, and vulnerability as inputs to impact-based