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Field
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EMBL-EBI - European Bioinformatics Institute | Hinxton, England | United Kingdom | about 2 months ago
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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of artificial intelligence and behavioral neuroscience. This individual will join our interdisciplinary team of computer scientists and behavioral neuroscientists seeking to identify the mechanistic and
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at Trinity College Dublin (TCD) seeks to appoint an outstanding, enthusiastic, and highly motivated Research Fellow who will contribute to a project that uses machine-learning methods to forecast
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are looking for a Postdoctoral Research Fellow who has: a PhD (or in near completion) in the relevant fields of Artificial Intelligence, Machine Learning, HCI demonstrated contributions to publications in top
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. • The ability to work independently and collaboratively within a multidisciplinary team. • Strong writing, critical thinking, communication, and presentation skills. • Experience in Machine Learning is a
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | about 2 months ago
data sharing (preferred); good knowledge of machine learning algorithms; proficiency in high-level programming languages (e.g., C++, Python, C#, etc.) (preferred); knowledge of database formulation and
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to engage with multidisciplinary teams and external partners. Desirable attributes include experience with spatio-temporal models, machine learning, Bayesian methods, and knowledge of environmental exposure
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for a Arcus Foundation funded project entitledGibbon acoustic monitoring Lao PDR. The primary duties will be to develop a deep learning-based call detector for gibbons from acoustic recordings
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, machine learning, and life cycle assessment, we aim to create sustainable wearable systems to enhance human well-being. For more details, please view https://www.ntu.edu.sg/mse/research . We are looking
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-sensor hyperspectral data for crop disease detection and monitoring. Develop machine learning or physics-informed models to retrieve reliable spectral and/or biophysical features, from multi-scale