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interest to identify cancer drivers from genomic data using machine learning (Mourikis Nature Comms 2019, Nulsen Genome Medicine 2021), study their interplay the immune microenvironment (Misetic Genome
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, to the rigorous study of quantum many-body problems. The successful candidate is able to actively contribute to the research profile of the Faculty of Physics, teach courses (max. 4 hours/week per semester), and
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no.: 4331 Among the many reasons to research and teach at the University of Vienna there is one in particular, which has convinced around 7,500 academic staff members so far. They see themselves as
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you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD degree (completed or in the final stages) in sociology, social policy
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computer codes to solve some of the daily research problems and have experience with high performance computing. You should have a PhD in Chemistry, Physics or Materials Science with a proven research track
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R or equivalent skills in another relevant language. We are not expecting you to be an expert in all forms of computer simulation, Large Language Models, or machine learning etc, but a working
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design, delivery, and evaluation of a multi-school research study investigating the impact of mathematical storytelling on secondary students’ mathematics learning and related outcomes. Working closely
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completion) in AI, Machine Learning, Data Science, Control or Energy Systems Engineering, or a related field. Strong expertise in AI for real-time systems, predictive analytics, or Digital Twins. Experience
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strategic dissemination, ultimately aiming for widespread adoption and commercial success. If you are still awaiting your PhD to be awarded you will be appointed at Grade 6, spine point 30. Upon written
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sustainability, performance, and reliability. Our research leverages optimization techniques, applied machine learning, and statistical analysis to achieve these objectives. Through the DecAI project we will work