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computational, theoretical and/or observational projects, to develop and deploy cutting-edge machine-learning and AI methods for astrophysics and cosmology, enabling precision tests of fundamental physics with
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Applications: Applying machine learning or AI to predict gene function or discover functional relationships from perturbation data. Familiarity with proteomics-specific public repositories (e.g., PRIDE) and
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experience in software testing a plus. Documented experience or interest in Artificial Intelligence and Machine Learning development, Proficiency in written and oral communication in English Additional
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involve collaborating with our researchers to process occupational classifications, harmonize census data, develop machine learning models, run statistical models, and write research articles
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phenomena from the microscale up. The developed technologies will be validated in half-cells and full working batteries at industrial partners at TRL 6. Our objectives Multiscale modelling to better
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, contribute to a better world. We look forward to receiving your application! We are looking for up to two PhD students in trustworthy machine learning, with a particular focus on cybersecurity, privacy, and
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28 Sep 2025 Job Information Organisation/Company Karolinska Institutet (KI) Research Field Computer science » Systems design Computer science » Computer systems Computer science » Other Biological
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application! We are looking for up to two PhD students in trustworthy machine learning, with a particular focus on cybersecurity, privacy, and verifiability for AI systems, based at the Department of Computer
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sequences, with applications ranging from biogeographical mapping to paleogenetic reconstructions. The candidate will work jointly with Dr. Eran Elhaik to design machine-learning models that unlock
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of visualization and multimodal machine learning. Admission requirements The general admission requirements for doctoral studies are a second- cycle level degree, or completed course requirements of at least 240