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Field
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data processing descriptions or mathematical formulas. In contrast, combining LLMs with computer vision provides a more flexible framework for understanding and reproducing the computational pipelines
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Remuneration: $37,145 (tax-free RTP stipend) For scholarship procedures and conditions, please see: https://www.monash.edu/graduate-research/future-students/scholarships/scholarship-policy-and-procedures
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the running infrastructures. Using cutting-edge computer vision, wearable sensors, and citizen science, RUN2GETHER will capture large-scale, real-world data during running events and group runs. These data will
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links atomic-scale chemistry, mesoscale transport, and device-level performance, allowing researchers to test, predict, and optimize designs in a computer before building them physically. By improving
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CFD simulations, led to a shift from performance towards efficiency, defined more precisely as minimisation of computer resources required for a given simulation. Concomitantly, the objective
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, and communicate complex spatial environments? Do you hold a master’s degree in cognitive science, environmental psychology, human-computer interaction, geo-information science, or a related field, with
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cutting-edge computer vision, wearable sensors, and citizen science, RUN2GETHER will capture large-scale, real-world data during running events and group runs. These data will advance our understanding
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[email protected] Requirements Research FieldComputer scienceEducation LevelMaster Degree or equivalent Skills/Qualifications Degree in Computer Engineering, Computer Science, Information Technology, Systems
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 3 months ago
of scientific articles and the PhD thesis Additional activities : Participation and involvement in the ANR project Scientific mediation and communication Where to apply Website https://jobs.inria.fr/public
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learning, computer vision, or a related field; knowledge of affective computing, generative AI models, and deep-learning methods; proficiency in Python and experience with machine-learning libraries