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machine learning models that predict soil health and crop performance. The position will exploit datasets integrating biochemical and molecular soil parameters (with a focus on microbiome features from
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. The successful candidate will be joining the Quantum Optics Theory group led by Prof. Dr. Maciej Lewenstein. The successful candidate will work on Machine Learning research. Share this opening! Use the following
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resonance imaging) Fluency in English Experience and knowledge: Required: Experience in computer programming Expertise in Python programming for Machine and Deep Learning, e.g., sklearn, pytorch, tensorflow
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or equivalent Research FieldEngineering » OtherEducation LevelPhD or equivalent Skills/Qualifications Skills in acoustics (PhD in acoustics required) and acoustics software. Skills in machine learning and deep
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resonance imaging) Fluency in English Experience and knowledge: Required: Experience in computer programming Expertise in Python programming for Machine and Deep Learning, e.g., sklearn, pytorch, tensorflow
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of Barcelona and the largest of Catalan Institute of Health (ICS). A scientific environment of excellence, highly dynamic, where high-end biomedical projects are continuously developed. Continuous learning and a
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sustainability of biomaterial manufacturing through safe design methods, machine learning, and predictive life cycle assessment as well as developing machine learning and hybrid digital modeling methods, combining
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quality alarm protocols based on machine learning: thresholds, alert workflows, and response or shutdown measur. Analyze data (time series) and develop quality indicators to support municipal decision
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optimiser that accelerates both workflow efficiency and materials discovery. Main Tasks and responsibilities: AI4LSQUANT aims to accelerate quantum modelling by learning fast, accurate surrogates
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Infrastructure? No Offer Description Research line: Learning in single cells through dynamical internal representations. Job description: Develop theory, models and algorithms for identifying molecular encodings