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: Statistical signal/image processing, deep learning, machine learning, neuromorphic computing Good communication skills and an appropriate publication record are essential. Solid knowledge of Python and C++ is
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scientists, and researchers working on medical image analysis, machine learning, and audiology. Our recent work has focused on using deep learning to analyse temporal bone CT scans and brain MRI data in
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discipline (eg Statistics, Machine Learning, Biostatistics, AI, Engineering) with experience of developing and applying new methods. You will be able to develop research projects, with publications in peer
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods
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Agency (ARIA). The PROTECT project (Probabilistic Forecasting of Climate Tipping Points) brings together cutting-edge AI, statistical, and machine learning techniques with climate modelling, aiming
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will have or be close to the completion of a PhD in Neuroscience, Psychology or a closely related discipline. With in-depth knowledge of cognitive and computational neuroscience including motivation
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experience in Oxford Nanopore Technologies (ONT) sequencing and bioinformatics A track record of research in microbiome science, metagenomics, whole genome sequencing, big data analysis, machine learning, and
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area, with content covering robotics and machine learning, and excellent programming skills in Python. You should have research experience in either robotics or machine learning. You should also have
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position from 01.10.2025 of a Postdoc Position at the Research Group Data Mining and Machine Learning at the Faculty of Computer Science, University of Vienna under the supervision of Prof. Claudia Plant
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sleep; performing anatomical tract tracing; analysing existing and new datasets using python and Matlab using advanced statistical methods such as machine learning; collaborating with other members