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coursework and GitHub repositories. Postdoctoral candidates must have extensive expertise in deep learning for medical image analysis. We welcome applications that only partially qualify these requirements but
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vegetation ecology. You have hands-on experience with ecological data collection and are proficient in data analysis and statistical methods. You are willing to travel to field sites across Europe, and
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conversational state of the art multimodal language analysis (such as motion capture and automatic speech recognition), as well as neuropsychological, psychological methods related to multimodal language and
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conversational state of the art multimodal language analysis (such as motion capture and automatic speech recognition), as well as neuropsychological, psychological methods related to multimodal language and
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interview analysis). - Experience as audiovisual translator is a distinct advantage. - Knowledge of Dutch and Spanish is an advantage. Other language combinations can be considered for the post. - Experience
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opportunities for training in a range of linguistic, and conversational state of the art multimodal language analysis (such as motion capture and automatic speech recognition), as well as neuropsychological
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research question(s); how you would approach answering these questions (i.e. a preliminary research design, appropriate data, and analysis methodologies); and what you consider to be the academic (empirical
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research question(s); how you would approach answering these questions (i.e. a preliminary research design, appropriate data, and analysis methodologies); and what you consider to be the academic (empirical
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research projects with high-level technical expertise. Exploring AI-based methods for imaging analysis and dose verification (depending on your experience). What you will do As a postdoctoral researcher, you
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analysis and dose verification (depending on your experience). What you will do As a postdoctoral researcher, you will: Independently carry out experimental and computational research within