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recruiting an outstanding and ambitious postdoctoral researcher in computational biology to advance the integration and modeling of large-scale microscopy data using modern machine learning approaches
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). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep
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years according to central collective agreement. Full time position. Starting date as agreed. Placement: Uppsala For further information about the position, please contact: Ruisheng Xiong (e-mail
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) training personalized computational models in new contexts, and (iii) studying in-silico clinical intervention strategies. The postdoctoral fellow will have the opportunity to: Learn about computational
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contact information (e-mail and telephone) to two reference persons who have agreed to act as reference for you. Please also describe the relationship with that person. The application can preferably be
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main duties involved in a post-doctoral position is to conduct research. Teaching may also be included, but up to no more than 20% of working hours. The position includes the opportunity for three weeks
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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
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on development of novel computational methods with state-of-the-art machine learning for gaining fundamental insights into healthy and diseased human tissues of the heart, cardiovascular system, and
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authority. Learn more about our benefits and what it’s like to work and grow at KTH. Trade union representatives Contact information to trade union representatives. To apply for the position Log into KTH’s
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. Our research is focused on cell biology, spatial proteiomics and machine learning for bioimage analysis. The aim is to understand how human proteins are distributed in time and space, how this affects