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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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in large pre-trained models (vision-language models), generative models (flow matching, diffusion), simulation-based inference, and robust and active learning. The group has a wide network of
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to collaborative projects / grant writing. The Barriga lab are a multidisciplinary group combining biology, physics and chemistry to advance our understanding of biological processes with a specific focus on
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higher education credits (ECTS). Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural networks, as well as courses in Python, GPU programming
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processes as well as the impact of biological processes on materials. Our ambition is to foster a dynamic teaching and research environment that is internationally recognized for its excellence in connecting
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professional experience and knowledge. Copy of diplomas and grades from your previous university studies. Translations into English or Swedish if the original documents have not been issued in any
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. Copy of diploma from your PhD. Translations into English or Swedish if the original documents have not been issued in any of these languages. Your complete application must be received at KTH no later
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if supporting documents are discovered to be fraudulent. Submission of false documents is a violation of Swedish law and is considered grounds for legal action. (A) and (B) can only be certified by
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or automated data processing workflows Experience building APIs or data services for large scientific datasets Familiarity with the Model Context Protocol or similar systems for exposing data to AI tools and
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described. The project has three main objectives: (1) Use simulation models to make inferences on the role of sex ratio selection on sex chromosome evolution in a different meiotic drive scenarios, (2