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learning and simulation-based inference for searches for dark matter (or other “invisible” new physics signals) at the Large Hadron Collider, with the support of competent and friendly colleagues in
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machine learning for the next generation of AI models – uncertainty-aware foundation models, generative models and world models – with the support of competent and friendly colleagues in an international
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higher education teaching and learning. The purpose of the position is to develop the independence as a researcher and to create the opportunity of further development. You will have particular
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. The postdoctoral researcher(s) will join an international research environment at Umeå University, including Stat4Reg (www.stat4reg.se ), which develops statistical and machine-learning methods for register data
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Institutet our overall aim is to uncover fundamental features of normal and leukemic stem cell biology that can instruct new strategies for clinical surveillance and treatment in hematologic malignancies. Your
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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includes the opportunity for three weeks of training in higher education teaching and learning. The postdoctoral fellow will: Develop and maintain harmonized satellite time-series datasets (Landsat and
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education teaching and learning. The purpose of the position is to develop independence as a researcher and to create the opportunity for further development. The postdoctoral position includes a combination
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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will also have good opportunities to learn from and socialize with other postdoctoral fellows at the department. For more information about the department or division visit: https://www.slu.se/om-slu