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proficiency in English. Significant documented postdoctoral research experience. Significant documented research experience (e.g. from postdoc or doctoral studies) from another university/institute or relevant
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work will increasingly focus on wet lab experiments using cancer cell lines, organoids, and animal models, including imaging and molecular analysis. The project is well-suited for candidates with a
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Assistant Professor in artificial intelligence (AI) with a focus on precision medicine (PA2025/1776)
based on multimodal data that have the potential to result in a paradigm shift from focus on “prevention with one size fits all” to “precision prevention”, the latter meaning specific preventive therapies
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development work within the industry or other organizations is considered to correspond to a traditional postdoc visit to another university. an interest in and understanding of pedagogical development within
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considered to correspond to a traditional postdoc visit to another university. an interest in and understanding of pedagogical development within the subject field in question. interest in and insights
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examine at doctoral level and supervise Postdocs The assessment of pedagogic skills will consider the ability to: • plan, conduct and evaluate their own teaching at all levels • supervise and examine
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Spatial metaTranscriptomics methods and thus also handling of image data. The PhD student will interact with other team members to a large extent. For this purpose, we are looking for a PhD student with
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proficiency in English. Very good oral and written proficiency in Swedish. Significant documented research experience (e.g. from postdoc or doctoral studies) from another university/institute or relevant
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requirements Very good oral and written proficiency in English. Significant documented research experience (e.g. from postdoc or doctoral studies) from another university/institute or relevant experience from
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radar signals), (ii) Medical image analysis, and (iii) Machine learning/artificial intelligence. The group boasts extensive experience in fundamental research within computer vision, machine learning and