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Field
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of the Saez Rodriguez group is to acquire a functional understanding of the deregulation of signalling networks in disease and to apply this knowledge to develop novel therapeutics. We focus on cancer, auto
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techniques, or tight-binding approaches. Proficiency with major simulation packages such as ASE, Quantum ESPRESSO, VASP, CP2K, or LAMMPS, and their Python interfaces. Working knowledge of machine learning
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scientists, biomedical informaticians, clinicians, and public health researchers to develop deployable, trustworthy methods that improve patient outcomes and health system operations. Key responsibilities
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Research Fellow in AI for Healthcare (1 FTE) – ArcHub ICUSafeNotes-School of Computer Science 011287
breakthroughs into commercial healthcare solutions. In the ICUSafeNotes project, we are conducting research and development of multimodal machine learning models that includes ICU note summarisation and analysis
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-binding approaches. Proficiency with major simulation packages such as ASE, Quantum ESPRESSO, VASP, CP2K, or LAMMPS, and their Python interfaces. Working knowledge of machine learning techniques in
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within a Research Infrastructure? No Offer Description Introduction As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the
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standards and data protection regulations. This includes managing sensitive data correctly and guaranteeing that machine learning applications are developed with ethical considerations in mind. Participate in
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, Computer Science, Electronics Engineering or equivalent. Experience in one or more of the following areas: machine learning, deep learning, software-hardware co-design, computer system performance, design
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of classes, using Machine Learning (ML) techniques such as Decision Trees, K-Nearest Neighbors (KNN), XGBoost, Support Vector Machines (SVM), or Neural Networks. Explore and implement clustering algorithms
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dataset, GroupLens Research. grouplens.org [8] Statlog German Credit Data, UCI Machine Learning Repository. archive.ics.uci.edu [9] ERASER Benchmark, ERASER Project. eraserbenchmark.com [10] e-SNLI Dataset