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, foreseen in the application: 1-Development of the SUPERB framework 2- Definition of building classes and numerical models for physical vulnerability assessment 4-Definition of baseline data reflecting
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methods in Social Sciences, with proficiency in data analysis procedures such as visualisation, differential analysis, mixed regression models, structural equation modelling, and supervised and unsupervised
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qualifications: a PhD within within the field of microscale acoustofluidics postdoctoral experience within the field of microchip based acoustofluidics documented experience of COMSOL-modelling within fluid
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Classification Title: Post Doc Associate Classification Minimum Requirements: A Ph.D. in biomedical informatics, computer science or a related field. Working experience with large language models
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studies and interactive AI systems. This position will be funded based on an initial 2-year contract + 2 years extension. The key idea is to apply theories, models, and methods from psychology to improve
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core facilities. These shared resources enable high-resolution, high-throughput analysis of tissue samples from both mouse models and human cohorts. Our lab culture is centered on intellectual curiosity
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? Or would you prefer to develop our macroeconomic models? All of this is possible. The focus is on projects for industry, as well as the Dutch and European governments. You may also participate in larger
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Research Institute for Environmental and Occupational Health (IRSET - UMR_S INSERM 1085) | Rennes, Bretagne | France | 15 days ago
particles - in promoting inflammation and fibrosis, and work to identify specific biomarkers of exposure and associated risks in human and mouse models. Develop and evaluate therapeutic strategies to target
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postdoctoral fellow interested in gaining training and experience in disease modelling and transnational science. The successful candidate will lead collaborative efforts among basic and clinical researchers and
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such as the NEPS. Potential research areas include (but are not limited to): Item response modeling of achievement tests Analysis of process data (e.g., response times) to enhance competence measurements