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Field
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ICFO is offering a postdoctoral position to outstanding, highly motivated scientists, who wishes to contribute advance technologies that drive the clean energy transition. In particular, we seek to develop novel strategies that contribute overcoming critical resource bottlenecks in energy...
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literatures: collective behavior, cultural evolution, computational social science, mathematical psychology, network science, collective intelligence, HCI, or the sciences of institutions, organizations, and
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not required as part of this position. Required Qualifications: Strong mathematical background, including expertise in one or more of the following areas: machine learning, statistics, and algorithms
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: Candidate must have a strong quantitative background, with a PhD in computational biology, bioinformatics or related field including bioengineering, computer science, statistics, or mathematics. Strong
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, mathematics, physics, or a related field. The ideal candidate should demonstrate a record of publications in the area. Strong knowledge in machine learning, statistics and programming skills (R, Python
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testing experience can be valuable. Statistics and Mathematics: Machine learning (supervised and unsupervised) methodology and evaluation including discrimination vs. calibration measures and (hyper
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genomics, metabolomics, or microbiome analysis Computer science, particularly machine learning, artificial intelligence, data science, or computational biology Mathematics or statistics, with experience in
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on the resulting algorithms and pipelines. As an emerging paradigm, differentiable programming builds upon several areas of computer science and applied mathematics, including automatic differentiation, graphical
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engineering. Classes and student activities are conducted in English. Applicants are welcome and encouraged from relevant engineering disciplines, computer science, mathematics, and physics. The institute has
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integrity in the design process calls for a technical model of the product concept, i.e., mathematical models of the product and its in-service environment, which inevitably must incorporate the influence