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have a background in qualitative research and community engagement. An interest in patient engagement and participatory action is a benefit, and either experience in, or interest in learning mixed
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annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based approaches, machine learning) where
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, data sciences, or a related subject, ideally with a focus on utilising large-scale health/biomedical data and the application of advanced data analysis methods such as machine-learning. Equivalent
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, such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive pension benefits Working, teaching and research at ETH Zurich We value
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, Information Systems, or a related field with a strong research focus in machine learning, biometrics, or mobile computing. Proven experience in federated learning, privacy-preserving machine learning
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to develop and optimize scalable experimental protocols across diverse material families. This role is part of a multidisciplinary team integrating materials chemistry, machine learning, and autonomous
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models using frameworks such as PyTorch and TensorFlow. Research experience in medical image analysis using deep learning algorithms. Strong track record in machine learning, computer vision, and medical
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integration Key areas: § Metagenomic and 16S rRNA sequencing analysis § Single-cell RNA-seq and proteomic/metabolomic data integration § Machine learning and AI applications in microbiome data
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antigens, T cell receptor (TCR) and antigen interactions and their crucial role in anti-cancer immune responses. You'll leverage your strong background in computational biology, machine learning, and
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, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and grow'. We welcome you to join our community