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the Computer Vision Center at the Universitat Autònoma de Barcelona; the CVC is a center with over 150 persons working machine learning and computer vision research. The position is for 3 to 3.5 years, starting
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Professional experience Experience in ecological modelling, oceanography, environmental sciences, statistical computing or a related discipline (PhD in any of this fields is desirable but not required) Strong
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Relativity, and cosmological measurements using GWs such as Hubble constant and probes of inflation and phase transitions in the early universe. We are developing new data analysis methods like the use of deep
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assisting with in-situ TEM measurements, facilitating cutting-edge research in sustainability and energy fields. Part of the project will also include the development of deep learning frameworks for TEM image
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Relativity, and cosmological measurements using GWs such as Hubble constant and probes of inflation and phase transitions in the early universe. We are developing new data analysis methods like the use of deep
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students and other researchers on in-situ (S)TEM. Requirements: · Education: PhD in Chemistry, Physics or Material Science, or closely related fields, with a strong focus on nanomaterials and advanced
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scientist. Job requirements Professional experience Machine learning / Deep learning tools (pytorch) and predictive modeling Bioinformatics analysis of omics data Education and training PhD or equivalent
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. Familiarity with statistical modelling, machine learning and deep-learning Additional information: We offer: 🌐The opportunity to work with our state-of-the-art HPC infrastructure and to join a vibrant network
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assisting with in-situ TEM measurements, facilitating cutting-edge research in sustainability and energy fields. Part of the project will also include the development of deep learning frameworks for TEM image
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) participate in the monitoring at sea to acquire video and picture of the transplanted sites, (2) quantitatively analyse video to define species and functional diversity, species abundances and population size