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Field
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Your job Do you want to understand how precipitation extremes over tropical South America are changing in a warmer world? Do you like to perform data analysis on large atmospheric datasets? Then we
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. However, current estimates of methane emissions from inland waters to the atmosphere are highly uncertain because of limitations in long-term observational data and modelling methodology. In this four-year
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system can reduce dependence on fossil fuels – but at the same time brings new challenges and uncertainties. Disruptive events and changing political, social, and technological conditions can have a
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and defects, with unprecedented detail. Through this work, you will uncover the fundamental links between synthesis conditions, microstructure, and macroscopic properties of layered materials. Your
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civil/electrical/control engineering or mathematics or related study programs with a solid basis in choice modelling and/or reinforcement learning, with knowledge of MATSim is advantageous. Description
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at around the time of implantation. To achieve this, the group utilises both in vivo mouse models as well as in vitro human stem cell culture systems and state-of-the-art ultrasensitive transcriptomic
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with colleagues at DTU and IIT Bombay, as well as with academic and industrial partners globally. The main purpose of this PhD position is to develop, implement and assess machine learning models
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will contribute to the enhancement and implementation of a digital model representing the Luxembourgish and cross-border energy landscape. The doctoral student will be a member of the Doctoral School
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dynamically over time. Second, clinical conditions such as infection, sepsis, ventilation, and hemodynamic instability are often interconnected, necessitating a holistic modeling approach. Third, there is a
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water basins across HMA. We will simulate future changes in temperature, precipitation, and snowmelt using climate projection models. These projections, combined with hydrological modelling, will allow us