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Field
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obtainable using the Oxford Nanopore sequencing platform and improve genome recovery from metagenomes by developing new binning algorithms based on machine learning. Furthermore, the postdoc will aid in
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/knowledge of computer science and/or machine learning Interest/knowledge of omics data analysis, gene regulation or structural modeling Proficiency in programming languages such as Python, R and/or C++ as
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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advanced machine learning methods for multimodal and 3D medical image analysis in musculoskeletal medicine, in close collaboration with clinicians and computer scientists. PhD or Postdoctoral Researcher
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We are seeking to appoint a Senior Postdoctoral Researcher in Statistical Machine Learning and Deep Generative Modelling to apply and develop cutting-edge deep generative probabilistic models
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start quickly and effectively, leveraging your experience in data analysis, machine learning and biomarkers quantification to contribute from the onset. You will liaise with external collaborators and
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with PhD and master students and with medical doctors. You will start quickly and effectively, leveraging your experience in data analysis, machine learning and biomarkers quantification to contribute
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parameter estimation Knowledge of advanced Bayesian methods and samplers, machine learning approaches to signal processing; additionally other methods such as simulation-based inference Good computing skills
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industrial partner, you will design and implement innovative architectures for real-time detection and control of laser processes. This interdisciplinary role combines artificial intelligence and machine
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of their research projects, fellows in the Smith lab have the opportunity to work one on one with the PhD biostatistician associated with our laboratory to learn introductory machine learning methodology such as