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WDM switches and the fast control to enable novel low latency highly scalable and flat interconnect AI compute clusters. Machine learning clusters and artificial intelligence (AI) training have become
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machine-learning approaches. Established markers such as neurofilament light chain (NfL) and GFAP will provide a biological reference point for identifying disease-specific biomarkers. A central part of the
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to achieve them. Acquire new knowledge quickly and use existing knowledge in new ways. Work constructively under pressure or in the face of adversity. Demonstrate strong problem-solving abilities with a
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Join the Responsible Machine Learning (ML) Group at the Faculty of Computer Science. Led by Prof. Dr. Martin Pawelczyk, who recently joined the University of Vienna from Harvard University, our research
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/coding and experimental hardware skills are desirable. Strong analytical and mathematical skills. Passion for research and willingness to learn. Good presentation, communication and scientific writing
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for candidates with a background in or demonstrated ability to learn about: Bayesian methods, probabilistic machine learning or inverse modelling. Prospective applicants are encouraged to direct informal inquiries
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/or QGIS) Very good English language skills, both written and spoken Basic knowledge of the German language or the willingness to acquire it for the purpose of knowledge transfer Openness, creativity
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argumentation deontic/normative reasoning decision- and/or game theory reinforcement learning A course the candidate has taken or a project the candidate has completed counts as documented background. Experience
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(WEFE) nexus, and model-based learning and communication. The group makes use of a variety of tools and techniques: stakeholder mapping, governance analysis, participatory modeling, non-linear feedback
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evaluation of pharmacological therapies under the supervision of Dr Rogier Min. At the National Research Council of Italy (CNR) in Cagliari, you will learn computational chemistry approaches to identify drug