283 data-"https:" "https:" "https:" "https:" "Simons Foundation" Postdoctoral positions in Sweden
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within the Data Science & AI division (DSAI). With 30+ nationalities and strong industry/academic ties, we offer a dynamic, collaborative ecosystem. The AI and Machine Learning in the Natural Sciences
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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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We are seeking a highly motivated candidate who has recently completed, or is close to completing, a PhD and has training in statistics, data processing, bioinformatics, or a related discipline, to
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interdisciplinary research environment More information about Jönköping University as a workplace, conditions and benefits on www.ju.se . Required Qualifications Applicants must have been awarded a PhD in Computer
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exposures and breast cancer risk. The focus of the project is on analyses of high dimensional and longitudinal data. The position is for three years, starting summer/fall of 2026 or upon agreement
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one signed letter of recommendation from referees who are qualified to assess the applicant’s research competence, Contact information for two referees who are willing to act as references, Other
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for advanced microscopy You will perform live-cell imaging experiments and analyze data You will collaborate with other members of the team in advance microscopy and super-resolution techniques You will develop
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values as a university and public 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
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-modal prediction models for breast cancer, using both medical images (X-ray, pathology) and clinical and tumor genomic data. The project AID4BC (AI-based Precision Diagnostics and Decision Support for
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. More information about the Division of Heat Transfer can be found here . Subject and project description Additive Manufacturing (AM) enables unprecedented design freedom for next-generation thermal