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at the intersection of genetics, epidemiology, and cardiovascular medicine. Using large-scale genetic and health registry data, you will investigate sex-specific differences in stroke risk among patients with atrial
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traffic flow theory and simulation. You are a machine learning enthusiast (and realist). You love coding and have proven experience in e.g. Python, Matlab, JAVA, C#. You can present and communicate your
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the inversion problem to reconstruct environmental properties using received signals from a variety of EM wave sourcies located in different positions. Propose and implement computationally efficient solution
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Assessment Model combining verifiable, self-reported and observable interaction data. Investigate how interviewers weight different sources of evidence and how cognitive, social and cultural biases affect
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up to 2050. Quantifying the environmental impacts of primary and secondary steel production under different future scenarios, including climate change, energy and resource use, water consumption, waste
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energy/water balance, evapotranspiration, thermal comfort, heat-health interactions. Solid programming and data analysis skills (e.g. Python, R, GIS). Willingness to travel for validation-related fieldwork
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research aims to understand the molecular, cellular and biophysical mechanisms that sculpt different tissue shapes and sizes to suit the lifestyle of the organisms. To achieve this goal, we are focusing
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, and increasing data complexity, as well as how monitoring approaches can be designed to remain effective across different marine contexts and scales. The successful candidate will contribute
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 2 months ago
are natural languages with their own grammar, structure, and rich visual-expressive features. Unlike spoken languages, they convey meaning through a combination of hand movements, body posture, facial
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preferences, individual differences, and the relationship between objective acoustic indicators and subjective perception. The resulting knowledge will guide the development of intelligent acoustic sensing