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for radiological breast cancer diagnosis. Our group has expertise in radiology, biostatistics and machine learning. In addition, we have a strong collaboration with research groups at KTH. Our international
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health. A concrete goal is to develop and design interpretable machine learning methods to predict and classify asthma and exacerbation of asthma. The aim is to improve respiratory health by designing
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. If there are special circumstances such as leave of absence because of illness, parental leave, position as elected representative in trade union organisations, military service or service/assignments relevant
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experience in image analysis, machine and deep learning, including completed courses in these fields, at the master and doctoral level of education, as well as first hand experience in method development
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. Experience of image analysis, machine learning or related fields. Practical experience of programming. An interest in multi-disciplinary research. Awareness of diversity and equal opportunity issues, with
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imagery, spectral analysis, time-series analysis, change detection, upscaling, data fusion, forest pests and diseases, environmental modeling, machine learning, and statistics are meritorious, as
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, environmental modeling, machine learning, and statistics are meritorious, as well as the ability of fast learning and critical thinking. The assessment will put particular emphasis on (1) your scientific
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in labour unions, etc. The candidate must have documented experience in image analysis, machine and deep learning, including completed courses in these fields, at the master and doctoral level of
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, clinical service, union assignments or other similar circumstances. Merits for this position are: Experience with natural language modelling (NLP) and machine learning. Experience of independent scientific
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experience in the area of Transportation Science, Knowledge Graph, and Machine Learning/AI (e.g., large language models). The postdoc will join a research team at KTH led by Dr. Zhenliang Ma. The postdoc is