11 big-data-machine-learning-phd-"https:"-"UCL" Postdoctoral positions at Nature Careers
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and enthusiastic individual who meets the following criteria: Recently earned a Ph.D. in bioinformatics, computational biology, computer science, electrical and computer engineering, or a related
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: https://obgyn.uchicago.edu/research/griffith-laboratory Required Qualifications: Qualifications needed for this position include a PhD in clinical psychology or a related field, such as psychology
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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Lab at Princeton University aims to recruit a postdoctoral fellow or more senior research position to work on projects related to the development of AI/machine learning approaches for chemical and
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computational biology/chemistry, machine-learning for biological or chemical data, metabolism, and drug discovery/design. Mentorship is taken seriously and every effort will be made to ensure the candidate is
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/performance trade-offs and typical RAN levers; experience with energy metering data is a plus. • Strong background in AI / Machine Learning for decision-making (e.g., forecasting, optimization with learning
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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terrestrial networks, non-terrestrial network entanglement distribution. Your profile PhD degree in wireless communications, signal processing, machine/deep learning or a closely related field in Electrical and
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, leadership, and data science. Special training for writing successful ERC Starting Grants as a ‘ticket’ to an outstanding academic career. Being part of a thriving academic and social community in Vienna, one
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hold a PhD in oceanography, marine ecology, computer sciences, data sciences or similar. We expect that you have: Expert knowledge on network modelling, especially aimed at ecological applications Strong