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multiple tasks and deadlines, work independently Commitment to ethical standards in research and academic conduct Ability to familiarize quickly with new research fields, topics, and methods We offer
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functional data ”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case
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the applicant as most relevant must be attached to the application. If it is difficult to identify the contribution of the applicant in multiple-author publications, a short explanation about the applicant’s part
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, ethnicity, religion, worldview, disability, sexual orientation, gender identity, gender expression, and age. We encourage women to apply. If multiple applicants have approximately equivalent qualifications
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to an interview. We hope that you will apply for the position. The application must include Cover letter, describing your motivation for the position, alignment with the project goals, and how you meet the required
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. We offer A unique research environment with multiple opportunities to develop research themes at the forefront of modern science A friendly, inclusive, and collaborative international working
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of applicants. The applicant must be notified if the request to be omitted is not met. We encourage men to apply. If multiple applicants have approximately equivalentqualifications, the rules pertaining
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on post-training and alignment of generative LLMs for lower-resource languages, including both data creation and model fine-tuning. The work will be performed in close collaboration with the industry
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Environment (from June 2025, the Centre for Global Sustainability). We welcome proposals for research that align closely with either or both of two externally funded projects that are starting in mid-2025
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. The applicant must be notified if the request to be omitted is not met. We encourage men to apply. If multiple applicants have approximately equivalentqualifications, the rules pertaining tomoderate gender quotas