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/publications/working-paper-series/Working-Paper-60-2025/SCRIPTS_Working_Paper_60_WEB.pdf ); (B) the ongoing SCRIPTS research projects (https://www.scripts-berlin.eu/research/research-projects/General-Research
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. Methodological Areas of Interest Applicants with experience in the following areas are especially encouraged to apply: Optimization (deterministic, stochastic, robust, reinforcement learning–based) Systems
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series of our coastal research projects enter a critical final or near-final phase which ends in autumn 2027. The researcher will carry out duties covering research, research management, and research
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analysis, time-series modelling, clinical prediction, risk modelling, survival analysis, causal inference, spatio-temporal modelling, or multimodal data integration. The candidate should be motivated by
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Additional Information Eligibility criteria - Remote sensing (applied to tropical forests) - Knowledge of (tropical) climatology is an advantage - Statistical analysis of time series (correlations, composites
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
desirable. Candidates with experience in time-series machine learning, advanced data analytics, and programming (Python) are especially encouraged to apply. Special Physical/Mental Requirements Special
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simulate the demand and supply. Based on agent-based simulations, a series of recommendations are made to reduce the gap between demand and supply on the job market. Furthermore, an online platform will be
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the demand and supply. Based on agent-based simulations, a series of recommendations are made to reduce the gap between demand and supply on the job market. Furthermore, an online platform will be developed
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conferences. ● Contribute to the intellectual life of the Laufer Center (e.g., seminar series, mentoring of graduate/undergraduate students) as opportunities arise. ● Other duties as assigned. Special
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emulation, active-comparator new-user designs, self-controlled case series and case-crossover studies, where appropriate. The role will also involve developing and validating clinical risk prediction models