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experimental chemistry, providing a supportive research environment. Applicants should have a PhD in Chemistry or related field, and extensive experience in python programming and machine learning models
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) Limited until: 30.04.2032 Reference no.: 5022 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique balance of freedom and support. Join us if you’re passionate
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will work as a member of an interdisciplinary team (including experts in machine-learning and microbiology) to establish microfluidics-enabled microscopy assays on single bacterial cells to determine
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frameworks and transformer architectures applied to biological sequences would be advantageous. You should have a PhD in bioinformatics, evolutionary biology, machine learning or similar. The post fixed term
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interdisciplinary team (including experts in machine-learning and microbiology) to establish microfluidics-enabled microscopy assays on single bacterial cells to determine their antibiotic resistance. Your work will
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including: Techniques to model domestic cooling demand. Proficient use of IES VE to model and simulate building energy systems. Use of machine learning techniques to forecast cooling demand. Proven ability
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(postdoc) Limited until: permanent Reference no.: 4984 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
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have: Experience with AI and machine learning for medical images Experience working with data from multiple hospitals An interest in rare disease research. Additional information Informal enquiries
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involve directed evolution and protein optimisation, applying molecular biology and biophysics. Researchers will be supported to develop skills in the latest AI or machine learning tools for protein design
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for analysis of large-scale bulk and single cell data sets Strong understanding of statistical modelling, data normalisation and machine learning methods applied to biological datasets Experience with data