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position within a Research Infrastructure? No Offer Description Samuel Kaski’s research group Probabilistic Machine Learning is searching for postdocs to work on AI fundamentals in exciting projects
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to bridge preclinical findings with clinical applications. Through advanced computational approaches, machine learning, and AI-driven neuroinformatics, we extract meaningful patterns from omics, imaging
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PhD students, Bachelor’s and Master’s degree students and interns, as well as taking part in scientific collaborations. As a Postdoctoral Researcher, you also have the opportunity to participate in
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design and analyse separation processes, develop data-driven or AI-assisted tools, or generate high-quality experimental data that supports method development, modelling, and machine learning. You will
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(PyTorch, Tensorflow etc.) Knowledge of multi-agent systems and autonomous agent modelling Expertise in Machine Learning and Artificial Intelligence We consider the following as an advantage: Willingness
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to deploy machine learning to support data analytics and complex decision-making processes. Knowledge of modern SW-tools in the area of energy and sustainability is highly beneficial. Your role and goals You
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active role in advancing the research projects of the MQS group. Our recent research has focused on the theory and applications of variational quantum algorithms and quantum machine learning. We also have
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. The concept has lately gained increasing interest from researchers in applied mathematics and machine learning. This is due to its remarkable flexibility, mathematical elegance, and as it has produced state
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topics. The department has a strong community on related topics: research groups working on digital health and wellbeing , network science , computational social science , and various topics in machine
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. The concept has lately gained increasing interest from researchers in applied mathematics and machine learning. This is due to its remarkable flexibility, mathematical elegance, and as it has produced state